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Some breakthroughs don’t start with a grant or a roadmap — they start with a question no one expects to matter. For JB, that moment was a cold email from a biologist he’d never met, asking if he could synthesize a molecule “when you’re back in Munich.”  That simple ask pulled a young chemist out of the fume hood and into the messy, electrifying world of live-cell biology. What followed — a trip to London, confocal imaging marathons, and a partnership built on trust and curiosity — reshaped both careers and helped unlock a new generation of GPCR imaging tools. This is the story of how collaboration quietly rewires a field. This collaboration would become the foundation of a GPCR imaging breakthrough that neither of them anticipated. How a Collaboration Led to a GPCR Imaging Breakthrough JB didn’t set out to contribute to a GPCR imaging breakthrough, but a simple molecule request set the entire trajectory in motion. He was a PhD student studying ion channels — living in a world defined by reaction mechanisms, synthetic routes, and the reassuring logic of chemistry. Then the unexpected request arrived. David Hodson needed molecules that were only one synthetic step beyond what JB was already making. The ask was simple; the impact wasn’t. That brief exchange connected two people who had never met but were equally driven by curiosity. When David later shared early data — including a moment where he realized he could image an entire islet — it became clear that this wasn’t just a small contribution. It was the start of a scientific partnership with the potential to shift how GPCRs could be visualized in their native environments. How Chemistry and Islet Biology Converged to Enable a GPCR Imaging Breakthrough The collaboration deepened when JB traveled to London, a trip that unexpectedly accelerated what would become a GPCR imaging breakthrough. What he expected to be a technical visit became a complete reframing of how he thought about biological systems. Instead of round-bottom flasks, he was looking at living cells under a confocal microscope. Freshly isolated pancreatic islets. Real-time calcium activity. Signaling waves pulsing across clusters of beta cells. Seeing those images, he realized just how different biological reality is from chemical idealization. Molecules weren’t abstract entities anymore — they were tools that could illuminate dynamic, excitable tissues and reveal mechanisms driving hormone secretion.That shift in perspective became foundational. It would later shape how he designed fluorescent probes, how he evaluated biological constraints, and how he approached GPCR imaging as both a chemical problem and a physiological one. How Chemical Probes Transformed GPCR Imaging and Outperformed Antibodies As JB continued exploring the biology, a major obstacle emerged: validated antibodies for GPCRs, including GLP-1R, were inconsistent and incompatible with high-resolution imaging. For a field that depends on understanding where receptors actually are — and how many are available at the cell surface — this was a major limitation. The shift toward chemical probes became a defining moment in achieving a true GPCR imaging breakthrough. Chemical probes offered a solution. They could be engineered to target surface-exposed receptors, remain stable across batches, support live-cell imaging, and tolerate super-resolution workflows. There was one challenge: JB had never synthesized peptides. The project required designing peptide–fluorophore conjugates that would bind GLP-1R with high specificity. Instead of stopping, he teamed up with a peptide specialist at the Max Planck Institute. Together, they built the first generation of GLP-1R fluorescent ligands — probes precise enough to visualize the receptor across islets, tissue slices, and ultimately living animals. Early images showed clean, bright labeling across whole pancreatic islets. That breakthrough launched the first wave of GLP-1R visualization studies and opened the door to deeper questions about receptor distribution, density, and trafficking. Designing Reliable GPCR Imaging Tools for Real Biological Systems Success brought new challenges. Chemical probes may be elegant, but biology isn’t. Tissue is messy. Cells behave differently day to day. Receptors internalize, traffic, recycle, and degrade. To build tools that performed consistently, JB and collaborators shifted toward a more rigorous parallelized screening approach. Instead of testing one compound at a time, they evaluated multiple probes in the same experimental conditions — same transfection, same cells, same humidity, same everything. This strategy accelerated discovery and reduced noise, helping them understand how each design change influenced labeling, specificity, and photophysical behavior. It also gave them confidence in how the probes would perform once shipped to external labs. The payoff was substantial. These optimizations enabled dual-color labeling strategies, surface-selective imaging, and ultimately in vivo visualization. These parallelized experiments were critical for turning early ideas into a reproducible GPCR imaging breakthrough. Two-photon microscopy experiments showed GLP-1R signaling in intact animals — a milestone that demonstrated just how powerful well-engineered chemical tools can be when paired with the right biology. Collaboration as the Driver Behind Today’s GPCR Imaging Breakthroughs Behind the technical success lies a partnership shaped by trust, shared energy, and a willingness to learn each other’s language. JB brought chemical intuition and a love for toolmaking. David brought deep experience in islet biology, calcium imaging, and tissue physiology. Over the years, they learned from each other in ways that shifted both careers. JB gained a grounded understanding of tissue heterogeneity, signal variability, and the biology that makes GPCR research challenging. David picked up unexpected chemistry insights — including a well-loved lesson involving acetonitrile in conjugation reactions. What made the collaboration durable wasn’t simply aligned expertise. It was a shared sense of fun, the kind of scientific joy that makes late-night imaging sessions feel lighter and big failures feel solvable. That chemistry — human chemistry — is what allowed the science to move as quickly as it did. Curiosity also played a central role. JB emphasizes how much of their progress came from staying open, asking questions freely, and engaging people at conferences regardless of title or reputation. Many of the connections that shaped the probes’ development came from simple conversations that began with genuine scientific interest. Their trust-driven collaboration is ultimately what allowed the GPCR imaging breakthrough to take shape. The Future of GPCR Imaging Breakthroughs: AI, Multiplex Tools, and In Vivo Discovery Today, JB leads an interdisciplinary group at the FMP in Berlin — chemists, theorists, biochemists, toxicologists, and cell biologists — all working toward the same goal: building better tools for visualizing cell-surface proteins, especially GPCRs. The work now stretches far beyond a single receptor. His team is exploring AI-enabled probe design, multiplex fluorescent strategies that allow visualization of multiple GPCRs at once, and approaches capable of mapping receptor crosstalk at nanometer scale. They’re also performing increasingly complex imaging experiments that capture receptor dynamics in intact tissue and live animals, expanding what’s possible in both basic research and translational settings. What started as one molecule request is now a platform vision — a future where any GPCR could be illuminated with high precision, in any tissue, across multiple colors, with tools designed as much by computation as by human intuition. And it all began with a simple moment of collaboration. This conversation is part of a three episode series produced in collaboration with our partners at Celtarys Research . If this behind-the-scenes story resonated, you’ll love the full conversation. 🎧 Listen to the full episode https://www.ecosystem.drgpcr.com/dr-gpcr-podcast/chemical-probes-for-gpcr-imaging-and-internalization If JB's story resonates 🎧 Listen to part 1 of this series with Dr. David Hodson

Most GPCR programs don’t fail because of weak molecules—they fail because biology behaves differently than the assay implied. This week’s feature goes straight to the foundation: how system-level GPCR thinking  protects discovery teams from the costly misinterpretations that derail programs. If your work touches GPCR pharmacology, these insights aren’t optional—they’re essential. Breakthroughs this week: Eli Lilly cuts Zepbound prices; GNAI1 missense mutation study; rapid Gαs endosomal translocation. 🔍 This Week in Premium: Sneak Peek Industry insights:  Lilly cuts Zepbound prices; Lilly hits $1T valuation; Novo advances amycretin. Upcoming events:  Adhesion GPCR Workshop; GRC—Transporters, Ion Channels & GPCRs; MPGPCR Joint Satellite Meeting. Career opportunities:  Senior/Principal Scientist—GPCR Pharmacology; Principal Scientist—In Vitro Pharmacology; Research Associate—Biologics Discovery. Must-read publications:  Gαi1 neurodevelopmental mutation; Gαs endosomal signaling; primary cilia as transduction hubs. Terry’s Corner: GPCR Pharmacology Insights That Prevent Real Drug Discovery Failures Discovery collapses when teams assume stable, linear, receptor-to-response relationships. Dr. Kenakin’s AMA made the central point unmistakable: GPCR systems constantly reshape ligand behavior through coupling efficiency, receptor density, local signaling architecture, and physiological feedback loops. This is where system-level GPCR thinking  becomes a competitive advantage—long before a molecule reaches animals or patients. When you see the distortions baked into the system, you interpret your data differently and protect your program from preventable failures. What You’ll Gain Spot false confidence early  → Sensitivity differences can turn full agonists into partials or even antagonists depending on system load. Avoid misleading mechanistic labels  → NAMs, PAMs, and biased agonists behave in system-dependent ways that single assays cannot reveal. Translate potency and efficacy realistically  → Recognize when deviations reflect biology rather than compound failure. Premium Members get 67% discount when they join Terry’s Corner in 2025 Sharpen your interpretation skills ➤ Dr. GPCR Podcast: Chemical Probes for GPCR Imaging with Dr. Johannes Broichhagen Reliable imaging tools change how researchers see receptor behavior. In this episode, Dr. Johannes Broichhagen explains how next-generation fluorescent probes—designed with precise synthetic logic—enable deeper insight into GPCR internalization, trafficking, and surface organization. His work shows why chemical design can outperform antibodies and how rigorous assay validation bridges chemistry and biology effectively. What You’ll Learn Why peptide–fluorophore probes succeed where antibodies fail How parallel synthesis& testing accelerates probe optimization How surface-exposed receptor pools reshape interpretations of trafficking Listen to the episode ➤ High-Content Screening for GPCR Programs: Overcoming Assay Limitations with Fluorescent Ligands High-content screening (HCS) is now indispensable for GPCR workflows—especially when spatial context, trafficking behavior, and live-cell kinetics matter. But HCS only works when assays are built with rigor and powered by the right fluorescent ligands. This feature from Celtarys Research outlines how to structure an HCS workflow that avoids batch effects, imaging artifacts, and variability while delivering reliable, mechanistic data. What You’ll Learn Why traditional radioligand assays miss critical spatial and kinetic signals Five phases of a robust, reproducible HCS pipeline How fluorescent ligands strengthen specificity, relevance, and assay confidence Read the full HCS feature ➤ Why System-Level GPCR Thinking Changes Data Interpretation And How Dr. GPCR Premium Membership Gives You an Edge Premium gives GPCR scientists and biotech teams a single, trusted source of weekly insight that cuts through noise. Members access deep-dive lectures, expert frameworks, curated jobs, upcoming events, and classified more. It’s a system-aware resource built for researchers who need clarity fast—reinforcing system-level GPCR thinking  every week so your interpretations stay sharp and aligned with real biology. FAQ 🔹 What’s included? Weekly research, careers, and industry intelligence; GPCR University; 200+ expert talks; networking; and member-only discounts. 🔹 Who is it for? Researchers, pharmacologists, biotech teams, and decision-makers who rely on accurate, efficient, interpretation-first information. 🔹 Why now? GPCR innovation is accelerating—and misinterpretation compounds quickly. Staying informed today prevents the delays others won’t see coming. Don’t Fall Behind—Access the Edge You Need Already a Premium Member? 👉 Access this week’s full Premium Edition here ➤ What Members Say "I am a convert! I will keep Dr. GPCR and the offered resources in my work sphere." Help us reach more scientists by providing quick rating on Spotify or Apple Podcasts — and a YouTube subscribe. Spotify: https://open.spotify.com/show/1KQHbC2qhkRIrdgBDtiQVF Apple Podcasts: https://podcasts.apple.com/us/podcast/dr-gpcr-podcast/id1514231064 YouTube: https://www.youtube.com/@DrGPCR Want to support Dr. GPCR? 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The Cost of Confusion Let’s be honest. Most biotech pitches don’t fail because the science is weak. They fail because the story is unclear. 👉 A confusing pitch doesn’t just slow down progress. It silently shuts down opportunity. You might still get the meeting. You might still get a few questions. But behind the polite nods, your audience is checking out. Here’s the uncomfortable truth: 👉 People make up their minds in the first few seconds. If your pitch doesn’t immediately tell them who it’s for, why it matters, and what makes it different, then they start mentally moving on, even if you’re still speaking. The result? You walk out of the meeting thinking it went well. They walk out already forgetting what you said. 👉 And that gap between delivery and perception is where momentum dies. For biotech founders, this is more than a presentation problem. It’s a strategic vulnerability. Because if you can’t explain your value clearly, your audience assumes there is none. A clear biotech pitch answers three key questions immediately. If your audience has to guess, you’ve already lost the room. The Most Common Mistakes in Biotech Pitches Even the most brilliant science can get lost in a poor pitch. And most of the time, the issue isn’t style. Its structure, sequencing, and focus. 👉 Here are the most common gaps we see in early-stage biotech pitches, even from smart, well-prepared teams: 1️⃣ Starting with the science Founders often begin with detailed technical information, pathways, targets, and models. But your audience isn’t evaluating you as a researcher. They’re trying to understand the opportunity. 👉 Opening with mechanisms forces the listener to do all the work. They have to guess why it matters, what the application is, and whether it fits. ✅ Start with relevance, not results. 2️⃣ Using buzzwords instead of clarity Words like “platform”, “breakthrough”, or “transformative” feel powerful. But without concrete context, they’re empty. Your listener doesn’t want to be impressed. They want to understand. 👉 Replace vague claims with focused positioning: What does your solution actually do ? Who specifically is it valuable for? Why now? 3️⃣ No clear strategic angle You might explain what your technology is. But do you explain why it fits your audience’s world? ✅ Strategic fit is not assumed. It has to be demonstrated. If your pitch doesn’t address timing, portfolio alignment, or internal traction, the audience won’t do that thinking for you. They’ll smile. Nod. Then pass. 4️⃣ Forgetting to frame the next steps One of the most common gaps? No clear “what now”. You finish the pitch ... and wait. If your listener doesn’t know what to do next or who should be involved, the conversation stalls. ✅ A strong pitch ends with direction, not silence. These aren’t “presentation mistakes.” They’re symptoms of an unclear strategy. And the good news is, they can be fixed. Strong biotech pitches don’t just inform, they align. Every sentence should move the conversation forward. How to Fix the Gaps 👉 Fixing your biotech pitch doesn’t require a rebrand. It requires a realignment. The strongest pitches follow a clear, strategic logic, not just a narrative arc. 👉 Here’s a four-part structure that helps founders move from scattered storytelling to focused positioning: 1️⃣ Who it’s for ✅ Begin by clearly defining your audience or market. Avoid vague generalizations. When the listener knows exactly who your solution targets, they can immediately place it in their mental map. ✅ This clarity signals strategic focus and shows that you're not casting a wide net. It shows you’ve made deliberate choices about application, indication, or customer. 2️⃣ Why it matters ✅ This is about urgency and relevance. Instead of leading with technology, lead with the problem it addresses. ✅ Frame the situation in terms of what’s at stake, whether that’s patient outcomes, time delays, unmet needs, or inefficiencies. This immediately shifts the conversation from academic interest to practical significance. 3️⃣ Why it’s different ✅ Differentiation must be more than a claim. It has to be obvious, credible, and valuable. Make it easy for the listener to understand what sets your approach apart from existing solutions or current standards and why that difference matters. Without this, you blend into the noise. 4️⃣ Why it fits ✅ Your pitch should always reflect an understanding of your listener’s world. Consider their priorities, constraints, and objectives. If your message doesn’t show alignment with their strategy or timeline, they won’t engage, no matter how strong your science is. A great pitch makes it easy for the other side to connect the dots and move forward with confidence. This framework is not about simplification. It’s about strategic clarity. ✅ When your pitch follows this logic, it respects the listener’s time, builds trust fast, and moves the conversation toward real decisions. What Changes When Your Pitch Works When your biotech pitch lands, the difference is immediate and powerful. You stop pushing. People start leaning in. You stop explaining. People start connecting the dots for you. 👉 This is what clarity creates. A clear, strategic pitch doesn’t just share information. It communicates that you know who you’re building for, why now is the right time, and how your solution fits into something bigger than your own science. ✅ It shifts perception. From: “That’s interesting” To: “This is worth moving forward.” When that shift happens, follow-ups come faster. Stakeholders engage earlier. And opportunities become more structured, not just more numerous. Because a well-positioned pitch is not just about communication, it’s about leadership. 👉 You’re showing that you think in context. That you understand the system you're entering. That you’re ready to operate at the next level. And in the early stages of a biotech company, that’s often what separates promising science from real traction. So if your meetings keep ending with polite nods and no momentum, it might not be your data. It might be your framing. Reworking your pitch is not polishing. It’s focusing. And when you focus on what your audience actually needs to hear, you don’t just earn attention, you earn action. Strategic Takeaway: Clarity Wins. Fast. 👉 Biotech founders don’t lose opportunities because their ideas are weak. They lose them because their positioning is unclear. A strong biotech pitch isn’t about saying more. It’s about making your value obvious, fast. 👉 The goal is not to simplify your science. It’s to clarify its strategic relevance, in seconds, not slides. If your pitch keeps stalling, stop editing your deck. Start refining your message. Ready to Break Your Bottlenecks? If you're feeling the friction, indecision, misalignment, or slow momentum, it's not just operational. It's strategic. Attila runs focused strategy consultations for biotech founders  who are ready to lead with clarity, not just react to pressure. Whether you're refining your narrative, making tough tradeoffs, or simply feeling stuck, this session will get you unstuck, fast. 👉 Book a 1:1 consult and start building the mindset your company actually needs.

Discovery programs rarely fail because a molecule “did nothing.” They fail because a molecule behaved exactly as the underlying system allowed—amplified, buffered, redirected, or reshaped by layers of receptor biology that weren’t accounted for. The October 30th AMA with Dr. Kenakin  highlighted a fundamental truth: GPCR systems do not offer stable, proportional input–output relationships. Receptor density, constitutive activity, coupling efficiency, local signaling architecture, and physiological feedback loops continuously rewrite the connection between ligand engagement and measurable response. Teams equipped with deep GPCR pharmacology insights make different decisions. They design assays differently. They interpret deviations differently. And they avoid the costly surprises that appear when in vitro conclusions collide with human physiology. In this session, you’ll gain: How system sensitivity transforms potency, efficacy, and agonist classification. Why allosteric modulators require a fundamentally different strategic lens. How enzyme behavior introduces nonlinear risk even in receptor-driven programs. The sections below synthesize the key topics addressed during the AMA and highlight the GPCR pharmacology insights that emerged from Dr. Kenakin’s answers. Physiological Feedback Reshapes Pharmacology The dobutamine example resurfaced for a reason. Its clinical utility emerged from the interplay between β₁-mediated inotropy and α-mediated vascular effects that buffered reflex tachycardia. This wasn’t predictable from a one-pathway model—and as Dr. Kenakin  noted, it wasn’t designed. It was revealed only when the drug encountered the full complexity of the cardiovascular regulatory network. This is a core GPCR pharmacology insight:ligand → receptor → G protein is never the entire story. Physiological reflexes instantly counteract, amplify, or redirect receptor-level effects. Multi-receptor involvement—intentional or not—often dictates the phenotype. Biased agonism introduces additional layers where one pathway may mimic “reflex-like” counterbalancing of another. Dr. Kenakin revealed  practical ways to anticipate these system-level interactions before they appear as clinical liabilities. Allosteric Modulators: System-Conscious Control Orthosteric ligands displace native signaling and impose their own control. Allosteric modulators interact with the system already in motion, shaping the receptor’s behavior without overriding endogenous tone. Dr. Kenakin  emphasized that the key advantage is not subtlety for its own sake—it’s bounded pharmacology. Orthosteric dose increases drive continuously stronger responses; NAMs and PAMs have structural ceilings. For complex GPCR systems, this boundary is a strategic advantage: NAMs can only shift an agonist curve so far—dose escalation won’t produce runaway suppression. PAMs permit enhancement without replicating the liabilities of orthosteric agonists. Endogenous ligands remain part of the signaling equation, preserving physiological patterning. These are not “gentler” mechanisms—they are more system-aware  mechanisms, a crucial distinction in modern GPCR pharmacology insights. In this AMA session, Dr. Kenakin talked about  the specific allosteric properties orthosteric drugs cannot offer. Receptor Density: The Distortion Engine One of the AMA’s recurring themes was the impossibility of interpreting efficacy without system context. Efficacy is not a molecule-only attribute—it's a joint property of ligand and system. High-coupled systems inflate apparent efficacy; low-coupled systems expose its limits. Dr. Kenakin  showed how the same agonist can behave as near-full, partial, or even silent depending on receptor expression and coupling efficiency. This isn’t experimental noise—it’s biology. Dual-assay strategies (high and low sensitivity) are essential, not optional. Benchmarks anchor efficacy expectations to clinically relevant responses. Constitutive activity governs whether inverse agonism is observable or physiologically meaningful. These GPCR pharmacology insights become critical when translating in vitro behavior to tissue environments with radically different receptor density—and therefore different operational efficacy. Assay Volume Control: Classification Through Contrast Sensitivity doesn’t merely change the size of the response—it changes the apparent identity  of the ligand. An agonist in one system becomes an antagonist in another. A partial agonist appears neutral until expression or coupling is increased. Dr. Kenakin  highlighted historical β-adrenergic cases where tachycardia appeared only once compounds reached more sensitive human systems. This is why experts never classify ligands from a single system: The same molecule can occupy different mechanistic categories across assay contexts. Without contrast (low vs. high expression), misclassification is nearly guaranteed. Translation requires understanding where the ligand sits on the operational curve—not just where it sits in one assay. These are core GPCR pharmacology insights for preventing interpretive drift as programs move toward in vivo work. NAMs, PAMs, and Subtle Mechanistic Traps Modulators are frequently labeled correctly but characterized incompletely. Dr. Kenakin  stressed that low-alpha NAMs can resemble competitive antagonists unless deeper kinetic or concentration-range testing is performed. Common mechanistic traps: Alpha-driven effects misinterpreted as beta-driven, or vice versa. PAMs assumed therapeutically viable without verifying whether they amplify affinity or efficacy. Concentration ceilings misunderstood—leading teams to misjudge modulatory reach. For teams seeking fine-grained control over receptor output, these GPCR pharmacology insights determine whether a series advances or stalls. Enzyme Behavior: The Nonlinear Gatekeeper In GPCR programs, CYP interactions often appear late—usually too late. Dr. Kenakin  emphasized that CYP enzymes are inherently allosteric, meaning inhibitory behavior is probe-dependent, substrate-dependent, and often counterintuitive. These nonlinearities matter: Competitive inhibition decreases as substrate increases. Uncompetitive inhibition strengthens as substrate increases—opposite of intuition. A compound may appear benign with one substrate and problematic with another. Time-dependent inhibition adds another nonlinear dimension: once the enzyme is trapped, recovery depends on synthesis, not on clearance. These GPCR pharmacology insights ensure receptor-focused teams don’t underestimate the metabolic landscape their molecule must navigate. In this AMA session, Dr. Kenakin reveals  the substrate strategy needed for credible DDI assessment. Irreversible and Pseudo-Irreversible Binding: Mechanism Dictates Risk Irreversibility is not a single category. Dr. Kenakin  drew a sharp contrast between chemically reactive irreversible inhibitors and pseudo-irreversible tight-binding compounds. One carries broad off-target risk; the other behaves more like a high-affinity ligand with slow dissociation. Strategic considerations: CYP time-dependent inactivation is mechanistically distinct from GPCR irreversibility. Extremely strong binders can fail in structured tissues because they saturate the periphery and never penetrate the core. Lower-affinity alternatives may produce deeper, more therapeutically relevant coverage. These GPCR pharmacology insights refine potency-driven thinking into distribution-driven thinking—especially for oncology or compartmentalized tissues. In the full AMA session, Dr. Kenakin reveals  how teams choose between slow-off and true irreversible strategies. Ranking Partial Agonists Without Losing Meaning Chemists want a single number. Biology rarely gives one. EC₅₀ and Emax uncouple affinity and efficacy, making cross-agonist comparison unreliable. Dr. Kenakin  emphasized that only operational-model–derived ratios anchored to a benchmark partial agonist provide interpretable comparisons. Practical takeaways: Use a clinically relevant partial agonist as the anchor. Interrogate agonists across multiple receptor-expression states. Ratios—not absolutes—capture the true structure–activity shifts. These GPCR pharmacology insights are essential for directing chemistry toward the property that actually matters in vivo. Dr. Kenakin revealed  the decision workflow for ranking agonists with translational intent. Why Terry’s Corner Give You The GPCR Pharmacology Insights You Need Terry’s Corner gives discovery scientists direct access to weekly masterclasses from Dr. Kenakin , monthly AMAs, and a continuously expanding on-demand library focused on sharpening interpretation—not creating noise. It equips pharmacologists, discovery teams, and biotech leaders to see around mechanistic corners, recognize the nonlinear behaviors that define GPCR systems, and protect programs from subtle but fatal interpretive errors. GPCR innovation is accelerating, and those who invest in deeper GPCR pharmacology insights today will shape tomorrow’s breakthroughs. 40 years of expertise at your fingertips: Explore the full library ➤

Watch Episode #177 Some scientific breakthroughs don’t start with a grant or a perfectly architected project plan. They start with a chance email, an unexpected visitor at the door, or the moment a team realizes the question in front of them is simply too big for one mind. In research, including the GPCR world collaboration isn’t a luxury. It’s survival. The future of discovery will belong to scientists who know how to build the right partnerships and stay humble enough to let others’ strengths unlock their own. The GPCR Collaboration Mindset Behind Breakthrough Science Most researchers have a story about the moment they realized they couldn’t push their science any further alone. For Hodson, that moment came early. His career moved through veterinary school, immunology, neuroendocrinology, and finally into islet biology — each step revealing a simple truth: Complex problems require multiple minds. By the time his lab began dissecting the GLP-1 and GIP receptor landscape in islets and brain, the signal became undeniable. GPCR signaling wasn’t linear. It wasn’t clean. And it certainly wasn’t something a single lab could unpick with isolated tools. To understand how incretin receptors behave in intact tissue, Hodson needed people who saw problems differently — chemists, structural biologists, cryo-EM experts, genetics teams, and collaborators who could challenge his assumptions without ego. That mindset shaped his partnership with JB, the chemist who would eventually help his lab visualize receptors in living systems with far more precision than antibodies ever allowed. Their collaboration didn’t start as a big strategic play. It started with curiosity, openness, and the humility to admit that better answers required better tools — and those tools lived in someone else’s expertise. How GPCR Collaboration Bridges Chemistry and Physiology Great collaborations often begin where frustrations peak. For years, the GPCR community wrestled with unreliable antibodies. Some worked in one tissue but failed in another. Some detected off-targets. And some simply misled entire research programs. Hodson’s group felt the impact directly: imaging incretin receptors in intact islets and brain slices was nearly impossible. That changed when JB’s team walked in with a different lens. Chemists don’t look at receptors the way physiologists do. They think in functional groups, fluorophores, linkers, and binding pockets. And that perspective unlocked something powerful. Instead of forcing antibodies to do what they weren’t built for, JB’s group engineered fluorescent ligands based on known GLP-1 and GIP pharmacology. The result was a set of chemical probes that finally allowed researchers to visualize where receptors exist, how drugs access them, and what cell types respond. These tools didn’t appear because someone wrote “visualize GPCRs better” in a grant. They appeared because one lab’s bottleneck became another lab’s engineering challenge — and together, they solved something neither could crack alone. This collaboration reshaped the way Hodson’s lab studies receptor biology. It didn’t replace physiology with chemistry. It fused them, creating a hybrid view of receptor signaling that has now been adopted by labs worldwide. When GPCR Collaboration Makes the Data Finally Click Every long collaboration earns a breakthrough moment — often after months or years of confusion. For Hodson, that moment came with a protein he’d been tracking for a decade: vitamin D binding protein, a glucagon-related secretion from alpha cells. For years, the data made no sense. The signaling didn’t line up. The knockout behaved differently than expected. And interactions with GLP-1 pathways were inconsistent. Most scientists would have shelved the project. Hodson nearly did. The turning point came when the cryo-EM data arrived — a structure solved through the same collaborative network that had built the fluorescent tools. Suddenly, the anomalies aligned. The protein was interacting with GPCRs in a way that no single technique could reveal. Chemistry, imaging, physiology, and structure finally intersected. This is the power of collaboration in GPCR research: insights emerge when one group’s “weird data” becomes another group’s missing puzzle piece. And when those pieces come together, the field jumps forward faster than any lab could push it alone. Why GPCR Collaboration Is Essential for Modern Science Hodson makes the point bluntly: modern GPCR science requires specialists. You need genetics teams for variant interpretation, metabolic phenotyping facilities for in vivo work, structural experts for cryo-EM, chemists for tool development, and data scientists who can integrate everything. No one person can be excellent at all of it — and pretending otherwise slows discovery. The shift toward team science isn’t cultural. It’s technical. The questions are larger, the stakes higher, and the datasets more complex. Collaboration is not “nice to have.” It is the only path to meaningful discovery. And it’s not just about capability. It’s about trust — the kind of trust built when collaborators confirm your data, replicate your results, and call out your blind spots before reviewers do. Hodson and JB’s collaboration works not because their skills align but because their thinking styles differ. One pushes chemistry further. The other pushes physiology deeper. Together, they push GPCR science faster. The Future of GPCR Collaboration in Metabolic Research The next decade of metabolic research won’t hinge on a single target. It will hinge on the teams who can map GPCR signaling with precision and design therapies that fit real biology — not idealized models. From GLP-1 and GIP dual agonists to the growing field of GPCR-based delivery systems, collaboration will control the pace of innovation. Here’s where the biggest opportunities will emerge: Building receptor-specific delivery systems for gene or peptide therapeutics Mapping cell-type–specific GPCR signaling in metabolic tissues Using genetics to understand responder vs. non-responder profiles Developing muscle-sparing metabolic therapies by combining GPCR pathways Creating chemical tools that finally show how drugs reach their targets These aren’t solo-lab problems. They’re team problems — the kind that require chemistry, physiology, pharmacology, structural biology, computational modeling, and clinical insight working as one system. The labs that collaborate boldly will discover faster, validate better, and translate more effectively. This is where GPCR science is heading: toward deeper integration, shared tools, and partnerships that amplify what each discipline does best. This conversation is part of a three episode series produced in collaboration with our partners at Celtarys Research . If this story resonates with your work or curiosity, go deeper. 🎧 Listen to the full conversation with Dr. David Hodson

High-content screening (HCS) has become a cornerstone in GPCR and phenotypic drug discovery, enabling researchers to quantify cellular responses with spatial, temporal, and mechanistic depth. For GPCR-focused programs, the ability to visualize receptor localization, internalization kinetics, and ligand interactions in intact cells offers advantages that extend far beyond traditional biochemical or radioligand assays. Yet, despite remarkable progress, HCS workflows remain vulnerable to several performance-limiting factors: variable cell behavior, imaging artifacts, batch effects, and incomplete assay optimization. These challenges can obscure real biological signals and complicate the identification of robust hits. Overcoming them requires careful assay design and strategic use of the right fluorescent probes. In this blog, you’ll learn:  How HCS works and why it is increasingly central to GPCR-based drug discovery  The key phases of designing a reproducible HCS workflow  How fluorescent ligands strengthen assay robustness and biological relevance What Is High-Content Screening and Why It Matters for GPCR Programs High-content screening integrates automated microscopy, multiplexed imaging, and computational analysis to evaluate cellular responses under chemical or genetic perturbations. Unlike biochemical assays, which reduce biology to a single readout, HCS captures whole-cell phenotypes and single-cell heterogeneity. Modern HCS instruments combine robotics, high-speed imaging, environmental control, and image-analysis pipelines capable of extracting hundreds of features per cell. The resulting multiparametric datasets are well-suited for GPCR research, where receptor trafficking, spatial dynamics, and context-dependent signaling significantly influence pharmacology. For GPCR assay developers, HCS supports:  Quantitative visualization of receptor internalization and trafficking  • Live-cell kinetic measurements  unavailable to endpoint assays  Multiplexed assessment of pathway activation   Improved confidence in hit prioritization through phenotypic fingerprints HCS is also becoming critical in toxicity screening, mechanistic target validation, and ligand profiling—making it an essential tool across the GPCR drug discovery pipeline. Why Traditional Radioligand Methods Fall Short for Modern Screening Needs Radioligand binding assays have historically been the standard for GPCR pharmacology. However, their limitations become increasingly important as drug discovery moves toward high-information, high-throughput formats. Key limitations of radioligand assays include:  • No spatial information  — signals are measured in bulk, masking subcellular dynamics  • Low temporal resolution  — difficult to use in kinetic or live-cell experiments  • Regulatory and safety constraints  that complicate workflows  • High waste-disposal requirements  • Reduced compatibility with phenotypic screening frameworks By contrast, HCS-based ligand binding assays—especially those enabled by next-generation fluorescent ligands—support:  Repeated imaging for equilibrium measurements  High-resolution spatial localization  Multiparametric phenotypic profiling  Full compatibility with automated screening infrastructure  Safer and more sustainable workflows For GPCR researchers aiming to reduce ambiguity in early hit-finding, the shift from radioligands to fluorescent HCS assays offers substantial scientific and operational benefits. The Phases of a Reliable HCS Workflow Designing a robust HCS assay requires a structured, iterative approach. The following phases minimize batch effects, reduce imaging artifacts, and strengthen reproducibility. 1. Assay Design and Pilot Optimization Successful HCS begins with a clearly defined biological question and the careful selection of a physiologically relevant cell model. Pilot experiments are essential to optimize:  Cell density  Fluorescent probe concentration  Exposure times and illumination settings  Imaging channel configurations The goal is to achieve a high Z′ factor , reflecting assay robustness and dynamic range. Early optimization prevents later variability and sets the foundation for scalable screening. 2. Plate Layout and Sample Handling Automated liquid handlers and randomized plate layouts are used to minimize positional effects and edge-related artifacts. Incorporating internal controls, including known agonists or antagonists, allows normalization and facilitates detection of plate-level drift. Probe panels—such as lysosomal dyes or cytoskeletal markers—can be integrated to support multiplexed readouts and mechanistic interpretation. 3. Imaging Calibration and Acquisition These steps ensure that quantitative signals reflect biology, not instrument variation. Imaging instruments must be calibrated for:  Focus stability  Light-path alignment  Illumination homogeneity  Spectral separation Environmental control (CO₂, humidity, temperature) prevents drift during long acquisition runs. 4. Image Processing and Feature Extraction Once images are acquired, segmentation algorithms convert them into quantifiable data. Increasingly, deep-learning-based segmentation  is becoming the standard for capturing single-cell features such as morphology, intensity, and localization. Retaining single-cell data preserves heterogeneity and enables mechanistic analyses, particularly important for GPCR signaling where subpopulations often drive distinct responses. 5. Data Analysis, Normalization, and Hit Identification Dimensionality reduction, batch correction, and standardized normalization methods prepare data for hit selection. Multivariate scoring allows integration of multiple phenotypic features, improving the robustness of hit identification relative to single-endpoint measures. When executed as a unified pipeline, these phases ensure an HCS assay capable of supporting both exploratory phenotypic screens and targeted GPCR binding studies. Figure 1. Standard HCI experimental pipeline. (A) After experimental design, wet lab work is performed to acquire high-content cell images, which then require several canonical image analysis steps. Cell segmentation is optional, but it will allow single-cell profiling downstream. (B) After image featurization,  image-based profiling steps are performed to prepare data for downstream analyses. (C) This full pipeline is orchestrated by reproducible software tools to ensure data provenance and to enable benchmarking. Source: Way GP, Sailem H, Shave S, Kasprowicz R, Carragher NO. Evolution and impact of high content imaging. SLAS Discov. 2023 Oct;28(7):292-305.  How Fluorescent Ligands Strengthen HCS Assays: The Case of CELT-331 Fluorescent ligands are now considered the gold standard for image-based GPCR assays. Their ability to visualize ligand–receptor interactions directly in living cells produces data that are both more physiologically relevant and more reproducible than traditional methods. Key scientific advantages include: Physiological Relevance Fluorescent ligand binding occurs in intact cells, preserving receptor conformation, trafficking, and native membrane context—key variables for GPCR pharmacology. Cleaner Signal and Higher Specificity Modern fluorophores minimize background, enabling precise quantification of binding and displacement curves. Non-Radioactive Workflow By removing isotopes, researchers gain safer, more scalable, and more environmentally responsible workflows. Visual + Quantitative Data Fluorescent ligand assays generate both numerical values (IC₅₀, Kᵢ) and spatial information that clarifies receptor behavior under different ligand conditions. Case Study: CELT-331 in CB2 High-Content Binding Assays In CB2-expressing HEK cells, the fluorescent ligand CELT-331  produces precise membrane-localized binding signals. When combined with a competitor such as the CB2-selective partial agonist GW40583, displacement curves can be visualized and quantified directly through HCS microscopy. This approach improves readout clarity, strengthens data reproducibility, and enables kinetic or equilibrium measurements impossible in endpoint radioligand assays. Figure 2. CB 2  cannabinoid high-content competition binding screening experiments with CELT-331. CB 2 -expressing HEK cell lines are labeled with CELT-331 at 80 nM (right), while competition with the CB 2 -selective partial agonist GW40583 is studied (left) to measure competitor binding affinity.  For cannabinoid researchers, this capability supports:  Accurate CB2 affinity determination  Visualization of ligand binding dynamics  Scalable, reproducible high-throughput assays  A smoother transition from screening to mechanistic studies At Celtarys, these capabilities are provided as a complete CB2 HCS service—allowing teams to integrate fluorescent ligand technologies without needing internal imaging infrastructure or specialized assay development expertise. Conclusion High-content screening continues to reshape GPCR drug discovery, offering richer biological context, improved assay sensitivity, and more confident identification of lead candidates. But fully leveraging HCS requires rigorous assay design, careful imaging calibration, and the strategic use of high-performance fluorescent ligands. As shown through the CELT-331 case study, fluorescent ligand–enabled HCS workflows provide physiologically relevant, reproducible, and multiparametric insights that traditional methods cannot match. For teams working in GPCR pharmacology or cannabinoid research, these tools accelerate hit validation, reduce ambiguity, and support more data-driven decision-making across early discovery. Looking ahead, combining HCS with advanced probe design, scalable analytics, and expert scientific support will further strengthen its role across the drug discovery ecosystem. At Celtarys, we remain committed to enabling this transition and supporting researchers as they design and optimize their next generation of cell-based assays. 👉 Learn more about CELT-311 References Booij TH, Price LS, Danen EHJ. 3D Cell-Based Assays for Drug Screens: Challenges in Imaging, Image Analysis, and High-Content Analysis. SLAS Discov.  2019.  Lin S, Schorpp K, Rothenaigner I, Hadian K. Image-based high-content screening in drug discovery. Drug Discov Today. 2020.  Way GP et al. Evolution and impact of high content imaging. SLAS Discov.  2023.

Burning Cash Isn’t the Problem. Burning Alignment Is. Every biotech founder fears the day the cash runs out. You track the burn rate. You watch the runway shrink. You delay hires. You negotiate term sheets from a place of panic. But here’s what most founders miss. 👉 Cash isn’t your biggest problem. Misalignment is. Not the obvious kind either. We’re not talking about personality clashes or investor drama. 👉 We’re talking about the type of quiet misalignment that appears to be progress but feels like confusion . The team is moving. The calendar is full. The experiments are running. But when you zoom out, you’re not actually getting closer to your next strategic inflection point . That’s what we call the hidden burn . 👉 This post breaks down how biotech misalignment happens, what it costs you, and how to fix it before your runway disappears without a clear outcome to show for it. Scientific progress doesn’t guarantee startup success; strategic clarity does. Where Biotech Misalignment Starts 👉 Most misalignment doesn’t start with conflict. It starts with silence. You assume your CSO knows where you’re headed. You assume the board is aligned with milestones. You assume your cofounder sees the same finish line you do. They don’t. 👉 Biotech misalignment usually begins when scientific logic and business logic quietly diverge . At first, it’s just different vocabulary. Later, it becomes different roadmaps. And by the time you catch it, your burn rate is up and your traction is down. Here are the three most common sources of internal drift in early biotech teams: 1️⃣ Scientific versus commercial vision 👉 Your science team optimizes for validation. Your business team optimizes for traction. If no one owns the connection between the two, they pull in opposite directions . Example: You validate a biomarker for a broad indication. Your BD person starts framing it for a niche diagnostic use. The board expects an IND package. No one’s wrong, but no one’s aligned. 2️⃣ Founder-team decision asymmetry 👉 The founders make strategic calls in 1:1s or ad hoc Slack threads. The team only finds out when timelines shift. This breeds passive execution, second-guessing, and a lack of ownership . People stop thinking ahead because they don’t know what’s coming. 3️⃣ Silent conflict inside your SAB or board 👉 Scientific advisors disagree with your go-to-market direction. Investors push for speed. No one wants to say it out loud. You end up running two strategies in parallel . One in your deck. One in your team’s head. How Misalignment Drains Your Runway 👉 Misalignment doesn’t show up as chaos. It shows up as wasted momentum. Your team is working. Your lab is busy. Your timelines look full. But the wrong things are moving. Or the right things are moving in the wrong order. 👉 That’s how biotech teams burn through capital without hitting real inflection points . Here’s how it happens: 1️⃣ Duplicated effort 👉 Two teams think they’re building toward the same milestone. In reality, they’re solving different problems. You pay for both. You benefit from neither. Example: Your platform team is building a modular assay framework. Your clinical lead is already assuming a fixed diagnostic protocol. By the time it surfaces, you’ve lost two months of budget and alignment. 2️⃣ Milestone redefinition spiral 👉 The milestone was “complete preclinical package by Q3.”Then it became “optimize lead series.”Then “refine bioavailability model.”Then “add a secondary endpoint.” The date never changed. But the scope moved. And now your next raise is behind schedule. 3️⃣ Strategic dilution 👉 You keep adding just one more use case. Just one more backup program. Just one more exploratory study. Your story gets fuzzy. Your team gets stretched. Your capital gets fragmented. Investors don’t fund complexity. They fund momentum. And misalignment kills momentum in slow, silent, irreversible ways. Real biotech traction starts when decisions are driven by shared strategy, not disconnected deliverables. Fixing the Alignment Problem Before It Kills Your Strategy Biotech misalignment does not fix itself. It does not go away with more meetings, louder all-hands sessions, or rewritten pitch decks. 👉 It only gets resolved when you rebuild how decisions are made and what truly matters inside your company. 1️⃣ The first shift is reframing what you call a milestone. A milestone is not a scientific phase. A milestone is a decision point that moves your company in a strategic direction. If nothing changes after it, it was just a lab update. Not progress. 👉 If your roadmap is full of scientific deliverables but empty of decision triggers, you’re burning runway without building value. 2️⃣ The second shift is clarifying roles, not titles. Most biotech founders don’t suffer from having the wrong people. They suffer because everyone has a different idea of what their role actually is.   Your CSO is not your COO. Your SAB is not your operating committee. Your cofounder is not your board. When these lines blur, so do accountability and execution. 3️⃣ The third and hardest shift is restoring shared context. Not by overexplaining. Not by trying to align on every single choice. But by making the decision framework visible across the team.  People don’t need to vote on everything. They just need to understand what game they’re playing. Here’s the truth biotech founders miss. Alignment is not a culture topic. It’s a leverage tool. ✅ When you fix alignment, you free up speed, clarity, and execution, without adding headcount or budget. Realignment as a Growth Lever, Not Just a Fix 👉 Most founders treat alignment like a hygiene issue. Something to clean up when it gets bad enough. A background process. A soft skill. ✅ But in biotech, alignment is a multiplier. When your team is aligned, you move faster without more funding. You adapt quicker without losing direction. You communicate with investors without rewriting your story every month. ✅ Science doesn’t just advance. It connects to business outcomes. Some of the most promising biotech teams aren’t failing; they’re just stuck. They have strong early data and an even stronger burn rate. Everyone’s busy. No one’s clear. But the moment they shift from disconnected workstreams to a shared, milestone-driven roadmap tied to strategic decisions, not just scientific deliverables, momentum changes. ✅ Realignment unlocks clarity. Clarity attracts capital. And suddenly, it becomes obvious what to kill and what to scale. ✅ That’s the power of strategic realignment. It’s not just damage control. It’s how biotech companies move from drift to direction. Conclusion: Don’t Let Misalignment Drain Your Future Misalignment rarely announces itself. It doesn’t crash your system. It just slowly redirects energy, delays clarity, and erodes momentum. 👉 You don’t notice it until you’re out of time, out of cash, and out of direction. But if you catch it early and fix it decisively, alignment becomes one of your strongest strategic assets. 👉 Not because it makes everyone agree. But because it ensures everyone is solving the same problem. ✅ If your biotech startup feels like it’s moving but not advancing, the issue might not be speed. It might be a direction. Ready to Break Your Bottlenecks? If you're feeling the friction — indecision, misalignment, slow momentum — it's not just operational. It's strategic. Attila runs focused strategy consultations for biotech founders  who are ready to lead with clarity, not just react to pressure. Whether you're refining your narrative, making tough tradeoffs, or simply feeling stuck, this session will get you unstuck — fast. 👉 Book a 1:1 consult and start building the mindset your company actually needs.

Watch Episode #177 The Experiment That Was Never Meant to Succeed When David Hodson’s lab teamed up with chemist Johannes Broichhagen aka JB, the goal was bold and elegant: Create a photo-switchable ligand to remotely control GPCR signaling with light. This was the moment when photopharmacology felt like the future. The literature was buzzing. Labs were competing. The idea was simple — turn signaling on or off with a flash of light. Except: Nothing behaved. Receptor access was unpredictable. Tissue responses defied the model. They had a tool that did bind the GPCR… but not in the light-controlled way they wanted. Most labs would have stopped there — archived the data, moved on, written it off as a failed bet. They didn’t. Sometimes the things you think are going to end up on the cutting-room floor become the best work. Instead of abandoning the compound, the team did something different: they looked at what it could do, not what it failed to do. And that shift changed everything. The Moment a Failed Tool Became a GPCR Imaging Breakthrough What the compound did reliably do was label and bind receptors in living tissue — in a way that made receptor location and accessibility visible. This solved a long-standing problem in GPCR biology: You can't understand signaling if you can’t see where the receptor actually is. For decades, GPCR localization relied on: Antibodies of inconsistent specificity Fixed tissue sections Indirect signaling readouts Researchers in the field know this frustration intimately: an antibody works in one context and fails entirely in another. Knockouts don’t behave as expected. Live-tissue dynamics become guesswork. This accidental tool changed that. It enabled: Live-tissue visualization Cell-type-specific receptor mapping Validation in both the periphery and brain Being able to see receptor distribution is not just aesthetic — it shifts interpretation. For metabolic GPCRs (like GLP-1 and GIP receptors): Drug efficacy depends on which cells express the receptor Side effects are tied to where agonists bind Weight-loss and appetite effects often originate in precise brain regions, not just the pancreas This tool helped clarify: Which neurons respond Which cell populations drive therapeutic benefit Where not  to target to avoid adverse effects Why GPCR Imaging Tools Matter More Than Ever This tool could not have emerged from a single lab. It happened because Hodson and JB thought differently — and allowed the clash of disciplines to be productive. Hodson: physiology, disease context, and imaging logic JB: chemistry, ligand engineering, mechanistic boldness Their collaboration worked not because they were aligned — but because they were complementary. And importantly, they liked working together. We’re not here long enough to spend 30 years collaborating with people we don’t enjoy. This is the part labs often underplay: scientific culture shapes scientific possibility. Collaboration, Chemistry, and the Pivot That Changed the Project Goal:  Develop a photo-switchable GPCR ligand Result:  The switching didn’t work Observation:  Binding + localization were unexpectedly robust Reframing:  Use the compound as a visualization tool Impact:  Shared widely → now used globally to map GPCR activity in live systems The success wasn’t in the discovery. It was in recognizing that the failure was useful. The Larger Lesson for Scientists and Innovators This story isn’t just about a GPCR imaging tool. It’s about how translation happens. Experiments fail for reasons that contain information. “Negative data” isn’t negative — it’s directional. The most valuable outputs often come from the “wrong” projects. For Early-Career Scientists Don’t optimize your trajectory for papers. Optimize it for questions that won’t leave you alone. Scientific progress is rarely linear. But depth compounds. What Changed After This Data This imaging tool is now being used to: Re-evaluate where GLP-1 and GIP receptors matter most Clarify brain vs. peripheral contributions to metabolic therapy Guide how next-generation incretin drugs are designed Support cell-targeted conjugate therapeutic strategies It didn’t just solve a problem. It opened a new category of problems to solve more efficiently. Which is the real definition of impactful science. This conversation is part of a three episode series produced in collaboration with our partners at Celtarys Research . If this story resonates with your work or curiosity, go deeper. 🎧 Listen to the full conversation with Dr. David Hodson

Watch Episode #177 The Career That Was Never Planned To Focus on GLP-1 Hodson didn’t begin with the identity of “scientist” — and that’s the point. He grew up working on farms and initially aspired to operate heavy machinery  simply because it looked satisfying. Later, exposure to veterinarians working in agricultural settings inspired him to train in veterinary medicine, where he was introduced to physiology and pharmacology  for the first time. Those courses didn’t feel like career-defining moments at the time — just requirements to pass. But seeds planted early often germinate later. The real pivot came during clinical rotations. Surgery electives meant long nights, constant patient responsibilities, and unpredictable call schedules. Meanwhile, researchers in the building across the way turned off the lights at 6 PM. Hodson made what seemed like a purely tactical decision: choose a research elective to focus on exams. That choice led him to immunology research on pigs — and, eventually, to a PhD. Early decisions don’t need to be perfect. They need to keep you moving. Curiosity compounds. And paths reveal themselves while walking. Following the Data Into GPCR, Metabolic Disease and GLP-1 After his PhD, Hodson entered neuroendocrinology — the “interface” between brain and body. The work introduced him to hormonal signaling, appetite regulation, and cellular communication systems. But something was missing. Growth hormone disorders, while scientifically rich, were relatively rare. Hodson wanted to contribute to a disease that affects millions. That brought him to type 2 diabetes  — a condition affecting nearly every family, marked by social and economic disparities in care. Studying the pancreatic islet — specifically the beta cells  that release insulin — offered a unique model: Rich in GPCR signaling pathways Experimentally accessible Deeply relevant to metabolic disease and obesity This shift also aligned Hodson’s work with a major scientific wave: The rise of incretin-based therapies, especially GLP-1 receptor agonists, now used in diabetes and obesity management. You always need a scientific anchor — but you also need the courage to follow data where it leads. GPCRs Re-Enter the Story — Not as Theory, but as Tools GPCRs have always been powerful drug targets — yet challenging to drug. Receptor localization, ligand access, and intracellular signaling can look different in actual tissues vs. cell lines. For real translational understanding, you need to see  the receptor in context. Enter a long-term collaboration with chemist Dr. Johannes Broichhagen - aka JB  — which, amusingly, began when Hodson opened the door wearing cleaning gloves mid home renovation. That partnership eventually produced fluorescent GPCR tools  that allow researchers to visualize GPCR engagement in live tissues , including: Mapping where  GLP-1 and GIP receptors are expressed Observing which cell types  respond to different therapies Understanding why similar drugs perform differently in different patients These tools have now been shared with hundreds of labs , accelerating research in obesity, hypertension, platelet biology, and more. Collaborations don’t start with strategy decks. They start with people you actually like working with . Skills + respect + shared curiosity = long-term impact. The “Aha” Moment — Ten Years in the Making Many discoveries unfold slowly — dozens of experiments that don’t make sense yet. For Hodson, one sustained curiosity thread involved a protein released by alpha cells in the pancreas: Vitamin D Binding Protein (GC-globulin). It affected hormone signaling between alpha and beta cells, but the mechanism was unclear. The breakthrough finally came when imaging and structural studies revealed that this protein was interacting with GPCRs involved in metabolic signaling — explaining confusing data that had accumulated for years. Suddenly, the puzzle snapped into place. A long-running side project became a central insight. GPCR–islet signaling links extended beyond classical ligand models.Collaboration and long-term persistence proved essential to discovery. Sometimes the experiments you almost quit are the ones that matter most. The Future of GPCR Therapeutics in Metabolic Disease Even with GLP-1 and GIP agonists reshaping diabetes and obesity care, the biggest questions — and opportunities — are still ahead. Key next questions: Why do some patients respond better than others? Why it matters: Personalizing care depends on understanding biological variability. Emerging direction: Genetics + receptor-distribution mapping. How do we prevent lean muscle loss during weight loss? Why it matters: Muscle mass shapes longevity, resilience, and overall metabolic health. Emerging direction: Multi-target GPCR + myostatin-pathway combinations. Should patients stay on incretin therapies for life? Why it matters: Cost, tolerance, and long-term side effects will define real-world adoption. Emerging direction: Treatment sequencing + guided de-escalation. Can GPCRs act as “delivery ZIP codes” for targeted therapies? Why it matters: Cell-specific delivery reduces off-target effects and boosts efficacy. Emerging direction: Peptide–drug conjugates for precision targeting. The next breakthroughs will come not from new receptors , but new ways of engaging and combining the ones we already know. This conversation is part of a three episode series produced in collaboration with our partners at Celtarys Research . If this story resonates with your work or curiosity, go deeper. 🎧 Listen to the full conversation with Dr. David Hodson

Drug discovery often assumes receptor inhibition follows simple rules—agonist binds, antagonist blocks, and data fit neatly into predictable curves. Yet, any pharmacologist who’s pushed beyond textbook theory knows: biology rarely plays fair. Schild analysis remains one of the few conceptual anchors that can tell us when “simple” truly is simple—and when deeper receptor dynamics are at play. In this session, you’ll gain: A clear conceptual map of Schild analysis and its origins. Insights into applying it to partial, inverse, and hemi-equilibrium systems. Ways Schild plots reveal hidden complexities like allosterism and receptor heterogeneity. The Legacy of Schild Analysis Schild analysis was born from an elegantly simple equation published by Sir John Gaddum in 1937. That paper quantified how one drug could block another’s access to a receptor—a framework that Heinz Schild later formalized into the tool we use today. At its heart, Schild analysis isn’t about math—it’s about validation. It asks whether the antagonism observed is truly competitive  or if unseen factors distort the result. It quantifies the degree of agonist blockade using dose ratios . It infers the affinity (Kᵦ)  of an antagonist by linking concentration shifts to receptor occupancy. Its strength lies not in complexity, but in the rigor of its simplicity. In the full lecture, Dr. Kenakin reveals how Schild’s equation became the first real “receptor test”—a filter that separates mechanistic truth from experimental illusion. Simple Competitive Antagonism A truly competitive antagonist obeys four essential rules—each serving as a gatekeeper to validity. Criteria for genuine competition: Parallel rightward shift  of the agonist concentration–response curve. No reduction  in the maximal response (the receptor can still be fully activated). Linearity  of the Schild regression (log(DR–1) vs. antagonist concentration). Slope ≈ 1 , indicating equilibrium binding. In practice, these criteria test the purity of interaction. Deviations—like reduced maximal responses or non-linear regressions—signal confounding kinetics, receptor mixing, or non-equilibrium conditions. As Dr. Kenakin emphasizes, “Schild plots don’t just confirm competition—they expose when competition is an illusion.” When Rules Bend: Non-Ideal Systems Not every system plays by Schild’s rules. Some responses—especially in calcium assays or complex tissue systems—depress the maximum agonist effect. Others show subtle curvature or slope deviations. Here, the Schild plot becomes a diagnostic tool  rather than a checkbox test: Slopes >1  often mean incomplete equilibration; lower antagonist concentrations haven’t had enough time to bind. Slopes <1  may reveal allosteric modulation , where the antagonist binds at a secondary site. Curvature  can signify heterogeneous receptors  or mixed response mechanisms. These deviations aren’t failures—they’re clues. Schild analysis turns receptor pharmacology into detective work, spotlighting mechanistic fingerprints buried in dose–response data. Extending Schild to Partial Agonists Partial agonists complicate things—they activate receptors but less effectively than full agonists. When these same molecules act as antagonists, their curves shift not only in position but also in shape. In the full lecture, you will learn how to extract affinity even in this dual-behavior scenario: Focus on the parallel portions  of the curves. Derive dose ratios  from those sections only. Fit those points to the Schild equation for an accurate estimate of Kᵦ. Partial agonists don’t break Schild analysis—they refine it. The model’s flexibility accommodates both agonism and antagonism as long as the analysis targets equilibrium regions. Inverse Agonists and Hemi-Equilibria In systems with constitutive receptor activity , inverse agonists reduce baseline signaling. Schild analysis still applies—if used carefully. The depression of basal response  is accounted for by focusing on curve segments where inhibition behaves competitively. Even when maximal responses are altered, affinity constants remain extractable  from correctly chosen data regions. Calcium flux assays, though tricky, yield valid Schild plots when analysis excludes non-equilibrium maxima. These adaptations underscore Schild’s resilience—it remains one of the few analytical frameworks flexible enough to handle inverse agonists, partial agonists, and non-ideal systems without collapsing conceptually. The Quick Glance: pA₂ as Shortcut Sometimes, discovery projects don’t have the luxury of full curve analyses. That’s where pA₂ values  come in—a quick estimate of antagonist affinity from a single concentration. Defined as the negative log  of the antagonist concentration that causes a twofold agonist EC₅₀ shift. Under ideal equilibrium, pA₂ ≈ pKᵦ . Caveat: Without multiple concentrations, competitive nature remains an assumption. pA₂ is an elegant glimpse—but not the whole picture. It ’s a screening tool, not a substitute for rigorous Schild validation. Schild as a Window into Mechanism Beyond affinity estimation, Schild analysis acts as a window into receptor behavior . It can uncover what’s really  happening inside a complex system. Common revelations include: Mixtures of receptor subtypes  producing hybrid response patterns. Allosteric vs. orthosteric inhibition , distinguishable by the plateauing of effect. Incomplete equilibration , where kinetics distort linearity. In practice, a deviation in slope or curvature isn’t noise—it’s the receptor speaking. Schild analysis translates that language. Each non-linearity is a coded message about the true mechanism. Learn how to reframe Schild analysis not as a relic of linear regression, but as an early machine-learning algorithm in human form: trained to detect outliers that matter. From Equilibrium to Exploration Schild’s greatest value today isn’t computational—it’s conceptual. Modern pharmacology has powerful modeling software, yet Schild analysis remains the litmus test for mechanism . Its purpose extends far beyond its 1930s origin: It teaches equilibrium thinking—recognizing when binding truly stabilizes. It sharpens interpretation—distinguishing real affinity  from apparent effect. It encourages skepticism—forcing researchers to prove competition before quantifying it. In Kenakin's words, “Every slope, every curvature, every failure to fit—those are the whispers of the receptor.” Schild analysis remains the simplest, most revealing conversation we can have with biology. Watch the course trailer 👇 Why Terry’s Corner Weekly pharmacology lectures by Dr. Terry Kenakin, monthly AMAs, and a growing on-demand library help scientists sharpen fundamentals, challenge assumptions, and strengthen pipelines. Built for pharmacologists refining tools, discovery teams solving bottlenecks, and leaders seeking credible insight fast. GPCR innovation is accelerating—those who act now will define tomorrow’s breakthroughs. Explore the full library ➤

Welcome back GPCR Fans, Clean data can still mislead if the underlying assumptions aren’t tested. Schild analysis is one of the few tools that tells you whether your “competitive antagonist” is actually behaving competitively. This week, we help you tighten your interpretations and strengthen your decisions at the bench and in discovery. Breakthroughs this week: McGPCR multimodal model; Endocrine Metabolic GPCRs 2026; Pfizer–Metsera acquisition. This Week in Premium: Sneak Peek Industry insights:  Domain CMO; Pfizer–Metsera; Novo Nordisk strategy shifts. Upcoming events:  GPCR-TDD Europe; Pharmacology 2026. Career opportunities:  GPCR Biology; Protein Science. Must-read publications:  OX2R dynamics; GPR68 nociception. Terry’s Corner: Schild Analysis — Why It Matters Most assays show a clean rightward shift and we assume “competitive antagonism.” But if the underlying criteria aren’t tested, that assumption can quietly erode the reliability of your conclusions. In this week’s lesson, Dr. Kenakin breaks down why Schild analysis remains the gold standard for verifying true competition — and why misclassification propagates error across affinity estimates, mechanism claims, and downstream modeling. Watch the trailer 👇 What you’ll gain Validate the model behind the data.  Use the four canonical criteria to distinguish genuine orthosteric antagonism from apparent shifts that mask allosterism or non-equilibrium. Quantify affinity you can defend.  Apply dose-ratios and Schild regressions to derive Kᴮ or pA₂ values that won’t collapse under scrutiny. Catch subtle mechanistic drift.  Diagnose hidden effects like mixed receptor systems or slope deviations before they distort your interpretation. Premium Members get 50%+ discount  when they join Terry’s Corner. Access this week’s key insight ➤ Dr. GPCR Podcast: Visualizing GLP-1 & GIP Receptors in Islets and Brain Understanding incretin biology depends on more than ligand potency — it hinges on where receptors actually are, how they internalize, and how tissues interpret signals in real time. In this conversation, Prof. David Hodson walks through how his team uses fluorescence tools and chemically engineered ligands to map receptor distribution, internalization, and engagement across pancreatic islets and brain circuits. The result is a clearer view of how incretin-based therapies act in complex metabolic environments. Why this matters Receptor distribution shapes incretin hormone drug effects across islets and neural circuits. Visualization tools redefine our understanding of signaling in intact metabolic tissues. Fluorescent ligand engineering clarifies receptor behavior that cell lines can’t reveal. Who should listen Researchers navigating complex datasets, balancing innovation with assay rigor, or working across chemistry–pharmacology–physiology interfaces will find this episode particularly relevant. This conversation is part of a three episode series produced in collaboration with our partners at Celtarys Research . Listen to the episode ➤ Quick Links Assess GPCR Biased Signaling of Agonist How GPCR Collaboration Built an Innovation Engine From Pipettes to Platforms: The Evolution of GPCR Research How GPCR Spatial Signaling Sparked a Scientific Journey Molecular Creativity in Drug Discovery Why Dr. GPCR Premium Membership Gives You an Edge Premium delivers a clear, noise-free stream of GPCR intelligence every week: deeper analysis, classified industry updates, expert frameworks, curated job listings, on-demand lectures, and priority event alerts. It helps you stay informed without overwhelm, move faster with context, and make stronger decisions with fewer blind spots. With live GPCR University courses returning next year and platform capabilities expanding, Premium pricing will increase soon. Anyone who joins before the change is fully grandfathered  — your rate stays locked, and your whole team benefits as the platform grows. Dr. GPCR is a nonprofit organization , and Premium Membership directly supports our mission to make reliable GPCR education and community infrastructure accessible to scientists worldwide. For those who prefer to contribute outside of membership, one-time or recurring donations  also ensure these resources remain available and continue to expand. You also gain access to member-only discounts, full GPCR University content, and an integrated view of publications, events, insights, and opportunities designed to support your career, your lab, or your organization. FAQ 🔹 What’s included? The complete Weekly News digest, curated jobs and events, classified GPCR publications, industry intelligence, expert lecture archives, and member-only discounts. 🔹 Who is it for? GPCR scientists, translational pharmacologists, biotech discovery teams, and decision-makers who need concise, credible, high-value intelligence to stay ahead. 🔹 Why now? GPCR innovation is accelerating. Acting on the right signals today shapes tomorrow’s breakthroughs — and prevents delays others won’t see coming. 👉 Access all the complementary news ➤ Already a Premium Member?  👉 Access this week’s full Premium Edition here ➤ What Members Say “Dr. Kenakin is a leading expert in the field. Aside from his vast experience in drug development, not to mention his extensive publication record, Dr. Kenakin is a masterful teacher and communicator.” Stay informed, stay competitive, and elevate your GPCR decisions — become a Premium Member today. See you in the Ecosystem, Dr. GPCR Team

Your scientific thinking built the foundation, but leadership is what scales it. The Invisible Obstacle   👉 Brilliant science. Stalled progress. It’s a pattern we see far too often in early-stage biotech operations and startups. The experiments work. The data looks promising. But decisions lag, the team spins, and investors get nervous. Science isn’t the problem; scientific thinking is. What makes you excel in the lab can quietly sabotage your leadership in the boardroom. 👉 Scientific thinking  rewards depth, rigor, and precision. But in a startup, those same instincts to analyze deeply, minimize error, and delay action until “enough” data is in can kill momentum . 👉 Most founders don’t even realize they’re still running their company like an academic research group. They explain instead of deciding. They analyze instead of acting.   ✅  This post explores how scientific thinking can become a leadership liability and what mindset shifts are needed to evolve from research reflexes to CEO decisions.   ✅  You don’t need to abandon your scientific instincts. But you do need to adapt them if you want your startup to scale .     The 3 Golden Rules of Scientific Thinking — and Why They Break Down in Biotech Operations Leadership   👉 Scientific thinking trains you to be precise, methodical, and skeptical. These instincts are critical in the lab, but they often undermine leadership when blindly applied in a startup . Let’s unpack the three core “rules” most scientific founders unconsciously carry into their companies:   1️⃣ “Only act when the data is solid.” In research, acting on incomplete or shaky data can destroy your credibility. In startups, waiting too long for certainty can destroy your momentum . 👉 Biotech founders often delay critical business moves, hiring, BD outreach, or funding decisions, because the data isn't “mature enough.” But in business, decisions must be made under uncertainty . Clarity doesn’t precede action; it follows it.   2️⃣ “Eliminate error at all costs” Labs are built around error reduction. You control variables. You minimize noise. But startups are inherently noisy. Trying to eliminate all risk leads to overengineering and stagnation . 👉 Instead of shipping early and iterating, many scientific founders keep refining decks, processes, and team structures until they feel bulletproof. But by then, the window of opportunity has often closed.   3️⃣ “Deep analysis leads to better answers” Scientific training favors deep thinking. More analysis = better outcomes. But in leadership, depth without speed equals paralysis . 👉 Startups don’t reward depth alone; they reward direction and decisiveness . Over-analysis becomes a form of avoidance. And while you're analyzing, someone else is executing.   👉 Bottom line:  Scientific thinking is invaluable, but only when it’s reframed for the role you’re actually in. ✅ You’re not optimizing experiments anymore. You’re steering a company.     Startups Play by Different Rules — and Most Scientific Founders Miss That   A research lab is designed for precision. A startup is designed for progress. And that difference changes everything. 👉 Scientific thinking values thoroughness, error reduction, and complete data before action.  But in the startup environment, these instincts can quickly become liabilities. You rarely have perfect data. 👉 You can’t eliminate every variable. And waiting too long often means missing the moment. Startups demand something different: ✅ Clarity of direction even when the picture is incomplete. The ability to decide when no option is risk-free. The discipline to align a team without all the answers. Founders who keep operating like researchers often create internal confusion. They revise instead of committing. They analyze instead of align. They aim for perfect clarity, and in doing so, they delay momentum, erode trust, and weaken execution. ✅ Scientific thinking can make you cautious when your company needs decisiveness. Unless you update the way you lead, your startup will struggle to translate insight into impact.   Leadership isn’t in your lab notebook; it’s in how you decide     How to Know If You're Still Leading Like a Scientist   👉 Leadership isn’t a title. It’s a way of thinking. And if your thinking is still shaped by academic norms, your startup will keep running like a lab, not a company. 👉Scientific thinking is precise. Leadership thinking is directional. The transition between the two isn’t automatic, even for the most capable founders. It requires conscious shifts in how you process uncertainty, how you frame decisions, and how you lead people through ambiguity. Here are three questions to help you check in with yourself: 1️⃣ Do you delay or dilute decisions while waiting for more clarity? Real leadership often means choosing without all the answers. If you find yourself looping decisions or delegating them upward, you might be leaning on scientific habits to avoid risk.   2️⃣ Do you overvalue internal logic over external action? It’s tempting to refine the deck, rework the roadmap, or re-analyze the market. But leadership is outward-facing. It’s about choosing direction, enabling others to move, and owning tradeoffs with imperfect inputs.   3️⃣ Do you explain more than you align? Explaining a model is not the same as rallying a team. When your communication centers on logic and detail instead of clarity and momentum, your team stays in wait mode, and execution stalls.   ✅ The shift from scientist to CEO  is not about abandoning your expertise. It’s about realizing that your value now lies in decisions, not just in depth.     Strategic Takeaway   👉 Scientific thinking will always be your strength, but it must be reshaped to serve your new role. 👉 As a biotech founder, your impact no longer comes from precision alone, but from your ability to lead through uncertainty, prioritize progress over perfection, and turn insight into execution. ✅  Leadership is not the opposite of science. It’s what gives it direction.   Ready to Break Your Bottlenecks?          If you're feeling the friction — indecision, misalignment, slow momentum — it's not just operational. It's strategic. Attila runs focused strategy consultations for biotech founders  who are ready to lead with clarity, not just react to pressure. Whether you're refining your narrative, making tough tradeoffs, or simply feeling stuck, this session will get you unstuck — fast. 👉 Book a 1:1 consult and start building the mindset your company actually needs.

When you walk into a typical academic lab, the boundaries are obvious: this PI’s corner, that group’s benches, their grants, their silos. But in Melbourne, a quiet experiment challenged that model — and it worked. It wasn’t about whose lab it was. It was about what we could build together, recalls Michelle Halls. What emerged wasn’t just another pharmacology group — it became a collaborative engine for GPCR discovery . Turning Silos into Systems The early 2000s were not kind to exploratory pharmacology. Funding models rewarded independence, not shared resources. Most labs operated like small, competing startups. But at Monash Institute of Pharmaceutical Sciences, a different idea took root: what if collaboration wasn’t a last resort — but the operating system ? Michelle was part of a cohort that joined as postgrads in shared facilities, pooling reagents, ideas, and failures. Rather than carving out turf, they grew by designing around collective capacity . No one had their own lab. That meant no one could build a fiefdom — and everyone had to talk. Why This Matters GPCR research demands integration — pharmacology, structural biology, signaling pathways, high-content imaging. A shared environment lowers friction between these specialties, making innovation structurally inevitable rather than aspirational. This wasn’t just a clever idea on paper — it changed how science happened, day to day. Engineering Collaboration: The Monash Lab Model Traditional academic labs mirror feudal structures. The Monash model flipped that logic: Shared infrastructure, not duplicated equipment Centralized core facilities for receptor assays PhD students trained across multiple techniques, not just one pipeline Senior scientists embedded as “connectors” between programs This design had a strategic effect : talent density increased, but so did interdisciplinary surface area  — the number of conversations where breakthroughs could happen. What Happens When Labs Stop Competing Michelle credits this environment for catalyzing the GPCR signaling projects that shaped her early career. For Early-Career Scientists Don’t just pick a project — choose an ecosystem. The structure you train in often matters more than the experiment you start with. The Power of GPCR Collaboration: Funding as a Force Multiplier Collaboration sounds warm and fuzzy. But at Monash, it was also ruthlessly pragmatic . At Monash, GPCR collaboration wasn’t just a cultural value — it was a deliberate strategy to build capacity, infrastructure, and momentum. Instead of competing for multiple small grants, groups strategically pooled resources to build critical infrastructure once . That gave them capabilities others couldn’t match — from receptor biosensor platforms to live-cell imaging cores. Shared funding gave us leverage. Suddenly, we could do experiments that individual labs just couldn’t afford. This changed not just what got funded, but what was possible . The lab went from project-level thinking to platform-level strategy  — a critical shift for GPCR biology, where complex systems need integrated tools. What Changed After This Data The pooled funding model turned the lab into a magnet: postdocs, visiting scientists, and industry partners wanted access to infrastructure they didn’t have. This wasn’t luck. It was designed. Culture as Infrastructure: How Trust Was Built Collaboration at this scale doesn’t happen by chance. It’s engineered . The Monash team built rotational PhD cohorts  — students cycled through multiple groups in their first year, gaining technical fluency and social trust. Senior postdocs acted as bridges, not gatekeepers. Weekly seminars were mandatory but lightweight, designed to connect  rather than perform. Michelle notes that the absence of individual ownership over physical space or specialized equipment removed the incentives to hoard knowledge . Most GPCR discoveries aren’t blocked by science — they’re blocked by structures that make sharing hard. Monash turned structure itself into a collaboration tool. Beyond the Bench: Leadership, Luck, and Leverage Michelle is quick to note that none of this was perfectly planned. “There was a bit of luck,” she admits. Timing, leadership alignment, and a critical mass of motivated scientists converged. But luck alone doesn’t sustain an ecosystem. What mattered was how leadership leveraged luck into durable structure  — through funding strategies, talent pipelines, and open lab architecture. This ecosystem outlasted individual PIs  and became a GPCR innovation hub  with global reach. Mini Timeline: How the Model Evolved Year 0  — Shared lab space established; PI buy-in secured Year 2  — Core imaging and signaling platforms launched Year 4  — Pooled grants fund expansion and training programs Year 7  — International collaborations and industry partnerships take root Today  — Model continues to produce high-impact GPCR science What the Rest of the Field Can Learn The Monash model isn’t an Australian story. It’s a blueprint . Biotech teams, CRO alliances, and academic consortia face the same challenge: how to align incentives to make collaboration not optional but structural . GPCR science thrives in complexity — meaning no single lab or company can do it alone. This ecosystem design blueprint applies to biotech teams and academic consortia alike. Michelle’s story shows what happens when an ecosystem is built deliberately, not accidentally. And for those shaping the next generation of GPCR discovery — from AI integration to next-gen biosensors — the lesson is clear : build together or build smaller. Collaboration isn’t a feel-good story. It’s a competitive advantage. 🎧 Listen to the full episode:   Leadership, Luck, and GPCR Signaling 🔓 Join   Dr. GPCR Premium  for deep dives, strategic tools, and behind-the-scenes conversations shaping the GPCR field.

Watch Episode 176 The first time Michelle ran a cyclic AMP assay, she did it with a single-channel pipette, trays of melting ice, and the kind of focus that only comes from knowing one mistake could waste weeks of work. We’d spend hours sitting there with trays of ice, transferring one by one with samples to a 384-well plate. No robots. Just her, radioactive ligands, and steady hands. That’s not a story about nostalgia — it’s a snapshot of how GPCR research was built, on technique at a time . And it’s a reminder that the way we do science today wasn’t inevitable — it was engineered, learned, and fought for by people who believed the field could be better. The Era of Cold Fingers and Patience Back then, GPCR signaling experiments weren’t elegant; they were endurance tests. Michelle describes spending hours in the lab measuring cyclic AMP levels — without multi-channel pipettes or high-throughput plate readers. Assay samples were layered on trays of ice. These weren’t quaint inconveniences. They shaped how questions were asked. These painstaking manual workflows laid the foundation for what would become the evolution of GPCR research — a transformation that reshaped how scientists design experiments and interpret signaling. We were doing assays on ice, pipetting one sample at a time. Every step felt like it could make or break the result, The pace and precision of GPCR research today — from high-throughput ligand screens to real-time signaling readouts — are built on the discipline forged in those early manual workflows. When Technology Became a Force Multiplier The introduction of multi-channel pipettes, automation, and standardized readouts wasn’t just an upgrade — it was a turning point. Suddenly, questions that were too risky or expensive to ask in the “manual era” became accessible. Instead of a dozen wells, you could test hundreds. Michelle notes that the real shift wasn’t just speed. It was confidence. When technology reduced the cost of failure, scientists could push boundaries faster. Reading those first papers on GPCR signaling organization absolutely fascinated me — the idea that receptors could cluster and control specificity blew my mind. What Changed After This : High-throughput capabilities meant researchers could map GPCR signaling more comprehensively. The field moved from single readouts to integrated signaling landscapes, accelerating drug discovery timelines and expanding targetable receptor families. This leap mirrors what’s happening now in other parts of the field: platforms replacing isolated tools, enabling both reproducibility and creativity. Those early cyclic AMP assays weren’t just cold and slow — they were part of a bigger puzzle. The Mindset Shift: From Technique to Strategy Michelle reflects on how early-career researchers once prided themselves on “perfect hands.” Today, success depends less on manual precision and more on experimental design, data interpretation, and strategic collaboration . In other words: the craft moved up the value chain. Where once a well-run assay was the pinnacle, now it’s the foundation — a starting point for more ambitious questions about GPCR networks, biased signaling, and functional selectivity. For Early-Career Scientists: Don’t over-invest in proving your pipetting skills. The real leverage comes from mastering the strategy behind the experiment, not just the execution. As technology absorbs the “how,” human expertise shifts to the “why” and “what if.” The GPCR field needs thinkers who can direct platforms, not just operate them. Leadership, Luck, and the Lab The episode isn’t just about technology — it’s also about how careers are shaped in science. Michelle’s path wasn’t linear. Like many, it was a mix of opportunity, timing, and the courage to say yes before everything was figured out. Her career didn’t follow a straight line — it zigzagged through long nights, and calculated leaps. Technical mastery opened doors, but what kept her moving was knowing when to say yes before everything was figured out — and how to grow from great pipettor to PI. Mini Timeline: Manual assay years — technical rigor as foundation Technology boom — scaling curiosity Strategic shift — experiments as decisions Leadership leap — from pipette to PI The Evolution of GPCR Research Every generation of GPCR scientists inherits the tools of the last and builds the next. What started as hand-built assays on ice has become integrated platforms for drug discovery, systems pharmacology, and real-time signaling analysis. But the heart of the field hasn’t changed. It’s still driven by scientists asking hard questions — and refusing to accept slow answers. Technology accelerates science, but people direct it. And those who understand both the legacy and the future of GPCR work are the ones shaping the next era of breakthroughs. This isn’t just a history lesson. It’s a call to see your lab bench not as a constraint, but as a launchpad. 🎧  Listen to the full conversation with Michelle Halls on the Dr. GPCR Podcast 🔓 Get tools, deep dives, and exclusive insights with   Dr. GPCR Premium .

Watch Episode 176 She didn’t want to be in the lab. It was supposed to be just a summer project—routine pipetting, repetitive assays, a box to tick before moving on. But something shifted. A single experiment worked. Then another didn’t. And somewhere between the results and the unknown, curiosity turned into obsession. I didn’t expect to love it, says Michelle Halls. But the moment I designed my own experiment, I was hooked. The Accidental Beginning Michelle hadn’t mapped out a scientific empire. She was a student expecting tedium, not inspiration. Yet that summer research placement cracked open a new reality: the thrill of asking questions no one else could answer . Her early work didn’t involve groundbreaking receptor models or million-dollar grants. It involved making sense of messy data and realizing the power of not knowing . This moment—the first taste of scientific ownership—reshaped her trajectory. It wasn’t the result that mattered. It was the fact that it was my  experiment. Many GPCR scientists trace their origin story back to a single unexpected spark. Not a grand plan. A spark. For innovators building tools, platforms, or therapeutics, these origin moments are where tomorrow’s leaders are born. The Moment It Clicked Once the initial spark was lit, Michelle’s curiosity snowballed. Instead of dreading lab time, she found herself chasing questions late into the night. This shift—from passive observer to active investigator—wasn’t about external validation. It was about internal ignition. She moved from “What am I supposed to do?” to “What happens if I try this?” That transition defines every true scientist. It’s not about perfection. It’s about chasing a signal through the noise. For Early-Career Scientists: Your pivotal moment might not feel like fireworks. It might be quiet, subtle—an idea you can’t stop thinking about. Pay attention to that. What began as a quiet obsession soon demanded a bigger stage. Curiosity wasn’t just something Michelle felt — it started steering every decision she made. From Cambridge to Leadership That early curiosity led her to pursue a PhD in Molecular Pharmacology at Monash University, and later to train in single-cell biology at University of Cambridge. She went from reluctant intern to global researcher shaping how we understand GPCR spatial signaling. By 2011, she had established her own group within the Drug Discovery Biology theme at Monash Institute of Pharmaceutical Sciences, exploring how receptors control localised signaling, how disease hijacks these systems, and how to target them for therapeutic gain. Mini Timeline Summer Project  — Unexpected spark PhD at Monash  — From curiosity to expertise Cambridge Fellowship  — Precision meets scale Leadership at MIPS  — Turning questions into impact What Changed After This : Her scientific questions got bigger. Instead of “what happens in this cell,” she began asking “how do cells organize signaling at scale?” This pivot reflects a universal research truth: origin stories evolve—but the spark remains . Luck, Leadership & GPCR Signaling Michelle is clear: luck played a role. But so did choice. She built on chance moments with deliberate moves—grants pursued, labs chosen, collaborations built. She emphasizes leadership not as titles but as creating spaces where science thrives . For her, leadership in GPCR research is about enabling others to find their spark the way she found hers. It’s easy to call it luck. But luck only works if you say yes when the door opens. For innovators and biotech strategists, stories like Michelle’s reveal how scientific leadership emerges. Not from polished plans—but from patterns of curiosity, risk-taking, and mentorship loops. Why GPCR Spatial Signaling Is Changing Drug Discovery Today, Michelle leads the Spatial Organization of Signaling laboratory, asking a deceptively simple question: where  do GPCR signals happen—and how does location change everything? Her work sits at the intersection of fundamental biology and therapeutic strategy. By understanding how signaling is organized in time and space, her team is opening doors to next-generation GPCR drug discovery and precision targeting. Spatial signaling isn’t just a technical detail. It’s a new language for drug discovery. Knowing where  signals occur could unlock new therapeutic strategies, better efficacy, and fewer side effects. Built to Inspire The story of Michelle Halls isn’t just about a career; it’s about a pattern. Curiosity → Ownership → Opportunity → Leadership → Innovation. For young scientists, that summer moment is waiting. For biotech innovators, those sparks are the future workforce and idea engines. For GPCR research, leaders like Michelle are showing what happens when we follow the signal all the way. 🎧 Listen to the full conversation with Michelle Halls on  The Dr. GPCR Podcast 🔓 Want to go deeper? Join   Dr. GPCR Premium  for exclusive tools, deep dives, and expert access.

Innovative Approaches in GPCR Drug Discovery: Designing Precise Solutions for GPCR Challenges. Welcome GPCR Fans, Most pharmacologists are trained to chase targets. But what if the real opportunity lies in the chemical matter we throw at them? That’s exactly what Terry’s Corner delivers this week: a deep dive into molecular creativity, rational design, and the overlooked role of chemistry in innovation. Breakthroughs this week:  Orphan receptor GPRC5B in neurogenesis; Septerna’s pill-based weight-loss strategy; Atrogi’s new CEO announcement. 🔍 This Week in Premium: Sneak Peek Industry insights:  New alliances, pipeline shifts, and platform tech that could reshape metabolic drug development. Upcoming events:  Global GPCR summits and pharmacology forums shaping 2026 priorities. Career opportunities:  Discovery biology roles and training paths in GPCR signaling. Must-read publications:  Emerging targets, signaling dynamics, and acid-sensing receptors in disease. Terry’s Corner: Why Chemistry Still Rules For decades, discovery focused on targets. But drugs aren’t just biology—they’re chemical matter. And that matter shapes everything: selectivity, safety, efficacy, and innovation. In this new course, Dr. Terry Kenakin reveals how drug chemistry defines function, not just fit. What You’ll Learn on molecular creativity in drug discovery: • Why Nature Was First : From opium to antibiotics, nature’s molecules still outperform many designed compounds. • The Power of Structure : How privileged scaffolds and rational design open the door to dual activity and precision. • Cheminformatics to Biologics : GPCR-focused chemical design is evolving—fast. Learn what’s next. 🟢 Premium Members get 50%+ discount when they join Terry’s Corner. 👉 Access this week’s key insight ➤ Dr. GPCR Podcast: Leadership, Impact, and GPCR Signaling with Dr. Michelle Halls This episode goes beyond the bench. Dr. Michelle Halls dissects how spatial GPCR signaling shifts discovery—and how leadership, mentorship, and vision shape translational success. From cAMP to femtomolar ligands, she unpacks a career at the edge of precision signaling. Key Insights: • Receptor Localization Matters : Protein complexes pre-assemble at membranes, altering how ligands trigger responses. • Assay Development Gets Real : Fluorescent tools and real-world biology don’t always match. She explains why. • Training Builds Innovation : Her lab model at Monash is shaping the next generation of GPCR scientists. 👉 Dive into spatial pharmacology ➤ A Note From Yamina: Building the Next Chapter of Dr. GPCR If the past few years were about rhythm, 2025 is about systems. Yamina’s open letter reflects on how Dr. GPCR evolved from a grassroots effort to a global force in GPCR science—one rooted in connection, sustainability, and execution. Highlights: • The Foundry Arrives : R&D meets biotech with real-world acceleration, strategic consulting, and CRO matchmaking. • Premium Expansion : New courses, better UX, and full University access are coming—grandfather pricing ends in 2026. • Inclusive Growth : More access for developing nations, new instructors welcome, and global partnerships with impact. 👉 Read Yamina’s note ➤ Why Dr. GPCR Premium Membership Gives You an Edge Premium delivers curated, noise-free intelligence every week: deep-dive expert lectures, classified industry news, priority event alerts, job opportunities, and insider commentary—designed to help you move faster, smarter. Whether you’re designing the next assay, scouting a new therapeutic angle, or exploring career pivots, Premium helps you stay ready—without the noise. FAQ 🔹 What’s included? The complete Weekly News digest, curated jobs, upcoming events, classified GPCR publications, exclusive on-demand expert frameworks, and member-only discounts. 🔹 Who is it for? GPCR scientists, translational pharmacologists, biotech drug discovery teams, and decision-makers who need fast, curated, career-relevant intelligence to stay ahead. 🔹 Why now? The pace of GPCR innovation is accelerating. Those acting on the right signals today will shape tomorrow’s breakthroughs—and avoid delays others won’t see coming. 👉 Don’t Fall Behind—Access the Edge You Need 👉 Already a Premium Member? Access this week’s full Premium Edition here ➤ Voice of the Community “Thank you for bringing this course with Dr. Kenakin. I wish Dr. GPCR the best for the sake of promoting more educational opportunities that are sorely needed in the field.” No matter where you are in your GPCR journey, Dr. GPCR Premium is here to accelerate your next move. 🧭 Get smarter signal detection, sharper tools, and real-time intelligence—all in one platform. 👉 Become a Premium Member ➤

Pipeline Efficiency Begins With the Chemistry Itself Drug discovery pipelines often stall not because the target is wrong—but because the chemical matter  interacting with that target lacks the right properties to produce meaningful pharmacology. We obsess over target validation, signaling pathways, expression patterns, and disease relevance. Yet, far less time is spent scrutinizing the structural logic and origin  of the molecules we screen in the first place. This lesson asks a deceptively simple question: What if our molecules—not our targets—are limiting discovery? In this lesson, you’ll gain: A strategic view of how chemical scaffolds shape pharmacologic outcomes An understanding of new chemical sources beyond natural agonist analogs Awareness of how GPCR allostery and biased signaling are redefining drug design The Long Arc of Chemical Pharmacology The early history of drug discovery was rooted in nature . Extracts from plants, fungi, bacteria, and environmental microorganisms provided the first potent modulators of physiology. Opium, for example, was used for dysentery and relief of suffering as early as the 3rd century BC; its derivatives — morphine, codeine, papaverine — became cornerstones of modern therapy.  The natural world still holds enormous untapped potential . Less than ~15% of higher plant species, <5% of bacterial and fungal species, and only a fraction of marine organisms have been meaningfully explored.  Yet natural-product scaffolds come with costs: they are structurally complex, expensive to modify, often unpredictable in IP , and sometimes more difficult to optimize for modern pharmacokinetics.  Still, nature remains a treasure map — just one that requires more strategic navigation. The key question Terry raises: If natural scaffolds provided our starting pharmacology, what new scaffolds will define the next 50 years? Building on Known Pharmacology Medicinal chemists learned early that modifying endogenous molecules — hormones, neurotransmitters, and metabolic signals — could yield new drug effects. Adenine-derived scaffolds enabled selective adenosine receptor antagonists; tryptophan modifications led to somatostatin receptor ligands.  From these efforts emerged the concept of privileged structures : chemical backbones that show repeat utility  across GPCR classes and receptor families. Indoles, benzodiazepines, phenethylamines — each recurs because it “fits” biology well.  This was more than trial-and-error. It was early structure-based pharmacology. Dr. Kenakin highlights how hybrid molecules  — combining two pharmacophores into one scaffold — enable dual-modality treatments with unified pharmacokinetics  (instead of juggling two separate drugs with mismatched ADME profiles).  And occasionally, new chemistry emerges from an unexpected source: Side effects. Diuretic action discovered in sulfanilamide derivatives led to furosemide; sedative effects of early antihistamines helped launch antipsychotics.  Lesson:  The structure-response relationship is rarely linear — and observing the unexpected is part of the craft. Informatics Expands the Search Space for Chemical Drug Matter Advances in chemoinformatics  introduced large-scale similarity mapping, such as SEA (Similarity Ensemble Approach), which compares the chemical similarity of ligands , not the protein sequence of targets.  This is a philosophical shift: Instead of asking, “Which proteins are related?” We ask, “Which molecules behave as if they belong together?” This approach reveals: Hidden target overlap New therapeutic hypotheses “Off-target” effects that may be on-target opportunities This expands drug matter beyond the familiar and encourages deliberate exploration of chemical novelty, rather than incremental tuning of existing scaffolds. The molecule, not the receptor, becomes the guiding principle. Allostery and Biased Signaling Change the Game The most profound change in GPCR drug discovery is our expanding understanding of allosteric receptor function . GPCRs are not simple on/off switches. They are allosteric machines , able to shift conformational states in response to multiple binding influences.  This enables: Positive Allosteric Modulators (PAMs) — enhance natural signaling Negative Allosteric Modulators (NAMs) — attenuate signaling Biased agonists  — favor one intracellular pathway over another These are not analogs of natural transmitters. They are structural strategies for tuning physiology. This reroutes discovery toward: Functionally selective ligands Better therapeutic windows More predictable clinical behavior Allosteric modulation allows us to work with  biology’s dynamic systems instead of forcing orthosteric competition. Biologics Are Now Chemical Drug Matter, Too Proteins, peptides, and antibodies are no longer niche. They are mainstream pharmacology. They offer high specificity , favorable safety , and unique mechanisms , including GPCR modulation through agonism, internalization, or ligand scavenging.  Advances in formulation and delivery have overcome earlier pharmacokinetic limitations. Peptide GPCR therapies now address obesity, diabetes, cancer, neuroendocrine disorders, inflammatory diseases, and more.  The boundary between “small molecule” and “biologic” has blurred. What matters now is not the category , but the fit: Does the chemical matter support the therapeutic mechanism? Does it interact with the receptor in a way that biology can use? Core message: The receptor is only half the story. The molecule is the other half. Why Terry’s Corner Terry’s Corner is a continuously growing knowledge platform built for scientists who want sharper decision-making power in discovery pharmacology. Subscribers gain weekly lectures led by Dr. Terry Kenakin, monthly AMA discussions, and on-demand access to a library of expert GPCR teaching sessions. Members can also propose new topics, ensuring relevance to real-world discovery problems. This is strategic, method-proven insight for discovery teams, pharmacologists refining core skills, and R&D leads who need clear reasoning in a rapidly changing field. GPCR innovation is accelerating. Those who learn now will shape the drugs others spend the next decade trying to understand. 40 years of expertise at your fingertips: Explore the full library ➤ Subscribe to the Kenakin Brief to stay in the know ➤

Exploring the Past and Future: Insights from Yamina's Perspective on Dr. GPCR. Dear Dr. GPCR Community, If the past few years have been about finding our rhythm, this year has been about refining our systems  — and stepping confidently into what’s next. When we started Dr. GPCR, it was with a simple goal: to connect people who shared a passion for GPCR science and discovery. What began as a small, volunteer-driven initiative has grown into a vibrant global network — thousands of scientists, founders, students, and partners who now learn, collaborate, and move the field forward together. This year, we focused on building for sustainability  — strengthening operations, expanding partnerships, and refining the systems that make Dr. GPCR stronger, more connected, and more capable of supporting our growing community. We’ve shaped everything we do around three interconnected ecosystems: Free , Premium , and Foundry. Strengthening the Foundation You already know our Free Ecosystem  — the podcast, blogs, and Flash News that make GPCR insights accessible to everyone. These resources continue to bring the latest in GPCR science and industry updates to thousands across the globe. The Premium Ecosystem  — home to the Classified Weekly Newsletter , Dr. GPCR University , the Job Board , and the Event Board  — has evolved into a hub for deeper engagement. It’s where conversations turn into collaborations and learning becomes ongoing. Now, we’re expanding that circle with the Dr. GPCR Foundry  — our R&D and biotech hub designed to bridge GPCR science with execution. The Dr. GPCR Foundry: Science Meets Execution The Foundry is where we bring together biotech innovators, Venture Capital, CRO partners, and GPCR experts to help teams move faster — from idea to discovery — while reducing risk and increasing efficiency. One of its first pillars, Terry’s Pharmacology Corner , led by Dr. Terry Kenakin , continues to grow. Through Terry’s Pharmacology Corner , he shares decades of expertise in an accessible, on-demand format for scientists across academia, biotech, and pharma. Learners can study at their own pace, shape the curriculum, and join live monthly AMA sessions with Dr. Kenakin. We’re fortunate to partner with Dr. Terry Kenakin , a pioneer who helped shape modern pharmacology and deepen our understanding of GPCR function. Premium Members receive exclusive discounted access — making it easier than ever to deepen expertise directly from one of the field’s pioneers. The Foundry will also include Yamina’s Consulting Corner — a place for teams to get tailored scientific and strategic guidance that helps bridge discovery and development. And coming early next year: the CRO Bank , connecting GPCR-focused companies and teams with trusted contract research partners to accelerate progress. Premium: More Value, More Connection Meanwhile, the Premium experience  itself is getting a major upgrade. We’re redesigning the platform for smoother navigation  and preparing to relaunch Dr. GPCR University  next year — with new courses and instructors. For the first time, University courses will be included in Premium Membership , giving members full access to learning, connection, and discovery in one place. As part of these updates, a pricing adjustment is planned for 2026 — the first since Premium launched . Anyone who joins Premium before these changes go live will be grandfathered at their current rate , as long as their membership stays active, and will automatically receive access to all new benefits. We’re also reopening our instructor program  — welcoming scientists from across the community to teach new GPCR-focused courses. Whether you’re an established expert or an early-career researcher, you and your lab will receive a complimentary one-year Premium Membership  when you lead a course. Our access program for researchers in developing countries  continues as well: eligible scientists can apply for a 90% discount on Premium , and every Dr. GPCR University course reserves five complimentary seats for students from developing countries — no Premium membership required. Strategic Partnerships with Purpose Dr. GPCR’s mission has always been about connection — not just between people, but between ideas, technologies, and opportunities. Our strategic partnerships  reflect that mission. They go beyond sponsorship to bring tools and technologies directly to the researchers who use them , empowering scientists to move their work forward with the right resources in hand. Our partnerships with Celtarys Research  and Revvity are great examples — uniting innovation and application to advance GPCR research worldwide. We’re continuing to seek new strategic partners  who share our goal of supporting the GPCR community while strengthening discovery where it truly happens — in the lab. The Dr. GPCR Ambassador Program As we grow, we want the community to grow with us. Our Ambassador Program empowers community members to share Dr. GPCR resources, connect new scientists, and earn rewards  for helping expand access to GPCR knowledge. It’s our way of recognizing those who champion the mission — spreading GPCR insights, connecting peers, and bringing more researchers into the community. We’ll share how to apply — and the details — soon. Community and Connection Dr. GPCR isn’t just a digital platform — it’s a community. This year, we hosted in-person Happy Hours in Boston  (one even sponsored!) that sparked new collaborations and friendships. In 2026, we plan to host more of these gatherings and begin preparing for the first Dr. GPCR Retreat  — our largest in-person event yet, designed to bring together scientists, industry leaders, and innovators in one shared space. Looking Ahead As we move into 2026, our focus remains simple: keep building with purpose — strengthening what works, refining what can grow, and listening closely to our community along the way. Dr. GPCR is evolving — thoughtfully, inclusively, and sustainably. As we grow, we’d love to hear from you — and work with you. Whether you’d like to partner, teach, share tools and technologies, or simply offer feedback , your input helps shape what comes next for Dr. GPCR. You can always reach me at hello@DrGPCR.org  — and yes, we read every email. With appreciation and excitement, Yamina Berchiche Founder & CEO, Dr. GPCR About Dr. GPCR Dr. GPCR is a global platform dedicated to connecting GPCR scientists, industry experts, and innovators through research, education, and community. From free resources like the podcast and blog to our Premium ecosystem and Foundry initiatives, our mission is to advance GPCR science — together. Related Links 🔗 Explore Terry’s Pharmacology Corner → TerryKenakin.com 📧 Connect with us →   Hello@DrGPCR.org 📧  Learn About Partnerships →   Hello@DrGPCR.org

Watch Episode 175 When Jens Carlsson was a PhD student, he thought collaborations slowed science down . While experimentalists struggled for months with crystallography, he could pull a clean protein structure from the Protein Data Bank in a single afternoon and move on. Why wait for someone else’s bottleneck? That perspective changed the moment he entered GPCR research . Suddenly, computational shortcuts weren’t enough. GPCRs demanded something different: the integration of modeling, medicinal chemistry, and pharmacology . Docking scores were meaningless without assays. Predictions went nowhere without synthetic expertise. And most importantly, no single lab could cover the full terrain alone . Today, Carlsson is Professor of Computational Biochemistry at Uppsala University and one of the strongest advocates for an approach that too many labs still resist. In his view, collaboration is not a bonus or an optional supplement—it is the only way GPCR drug discovery works .   From Lone Modeler to Collaborative Architect Carlsson’s lab is built to plug directly into a larger ecosystem . At its core is a team of about ten computational chemists working on molecular docking, molecular dynamics, virtual screening, and more recently, machine learning. Supporting them is a medicinal chemist who can design and synthesize new scaffolds when commercial libraries run out of options. But Carlsson doesn’t try to do everything under one roof. For receptor assays and the biological interpretation of ligands, he relies on a network of collaborators worldwide , each bringing specialized expertise in different GPCR targets. The power of this design lies not in its independence but in its interdependence . Predictions from modeling inform chemistry. Chemistry fuels assays. Assay data flows back into models. The cycle only works because every part is connected .   Closing the Trust Gap If collaboration is so effective, why do so many labs avoid it? Carlsson points to a deeper problem: credibility . Experimentalists often hesitate to rely on computational predictions, especially when burned in the past by models that promised too much and delivered too little. Carlsson has learned that credibility doesn’t come from publishing a paper or showing a binding score. It comes from honesty. His group is trained to explain exactly what a model can predict and where its limits are. If docking can suggest binding modes but can’t resolve nanomolar potency differences, they say so. If a simulation narrows options but doesn’t rank them definitively, they make that clear. That candor changes the tone of collaboration . Pharmacologists know they aren’t being oversold. Chemists understand why certain molecules are worth the effort to synthesize. And experiments are better designed because expectations are realistic. Over time, that transparency has built enduring partnerships , including one of Carlsson’s earliest with Ken Jacobson’s lab at the NIH , which continues to advance GPCR ligand discovery today.   Beyond Academia: Advising Biotech Carlsson’s collaborative philosophy has also found a place in the biotech industry . Through his consulting company , he doesn’t simply sell computational services. Instead, he acts as an advisor, helping research teams decide where modeling can accelerate progress—and where it can’t. This distinction is critical. Many startups chase elaborate simulations that look impressive on paper but do little to move drug discovery forward. Carlsson helps teams avoid that trap by focusing on leverage points : which models can be trusted for a particular GPCR, which predictions justify immediate synthesis, and when the smartest move is to pause until better biological data arrives. In practice, this approach saves companies time, resources, and credibility with investors. It also allows Carlsson to stay plugged into the fast-changing needs of biotech while keeping his academic mission intact: training the next generation of GPCR scientists . The GPCR Challenge What makes collaboration non-negotiable in GPCR research is the biology itself. GPCRs regulate essential functions from vision to mood to cardiovascular control. They offer extraordinary therapeutic promise —but their complexity makes them one of the hardest targets in drug discovery. Biased signaling, allosteric binding sites, and subtype selectivity mean there is rarely a straight line from prediction to medicine. No single discipline can cover all the ground . Structural biologists may capture snapshots of receptor conformations, but lack large-scale screening capacity. Modelers can generate binding hypotheses, but they remain untested until validated experimentally. Medicinal chemists can synthesize molecules, but must choose carefully from infinite possibilities. The path forward depends on knitting these pieces together into a coherent discovery engine. Carlsson’s lab is a proof point : collaboration is not just a cultural preference. It is a technical necessity .   Lessons from the Collaboration Blueprint Carlsson’s approach offers lessons across the spectrum of GPCR science. At the individual level, progress begins with transparency . Overstating the precision of a model or the predictive power of an assay may look persuasive in the short term, but it erodes trust and slows progress in the long term. Equally important is the ability to learn across disciplines . A pharmacologist who understands docking, or a modeler who knows assay constraints, will collaborate more effectively and make fewer wrong turns. Science advances faster when people invest in fluency beyond their own silo . Finally, collaboration should be treated as a deliberate strategy , not an afterthought. The most effective discovery programs are structured like Carlsson’s: modeling designed with downstream chemistry in mind, chemistry connected to assays, and assay data cycling back to refine predictions. Whether in academia or biotech, the future belongs to research groups that can orchestrate ecosystems rather than defend territories .   Why His Model Works What sets Carlsson apart is not just access to computational power or assay platforms. It is the values he applies to every collaboration . He treats modeling as part of a continuum rather than a separate discipline. He resists hype, focusing instead on predictions collaborators can actually use. And he prioritizes shared purpose , designing each project with the next experiment in mind. These values have become the glue that holds his partnerships together . They explain why collaborators return, why projects move forward, and why his model of collaboration is increasingly cited as a template for how modern GPCR science should be done .   GPCR Models Don’t Discover Drugs—People Do In GPCR research, the biggest breakthroughs won’t come from algorithms or crystal structures alone. They will come from how scientists choose to work together . Carlsson’s lesson is simple but profound: the strongest model in GPCR drug discovery isn’t built on a supercomputer. It’s built on trust between scientists. And for the next generation of researchers and biotech leaders, that is the real collaboration advantage . Want to hear how Dr. Carlsson mentors the next generation? 🎧 Listen to the full episode on the Dr. GPCR Podcast 🌱 Build a career with purpose, not just papers The Dr. GPCR Premium Ecosystem  provides early-career scientists with real-world guidance, insider knowledge, and access to leaders in the field. 🎓 Mentorship that matters. 🧭 Decisions with clarity. 💬 Exclusive community.

Watch Episode 175 If your model can’t predict the future of GPCR drug discovery, why build it at all? For decades, GPCRs have been the cornerstone of pharmacology. Nearly one-third of all approved drugs target them. Yet even with the structural biology revolution, one stubborn hurdle persists: prediction.   Can we leverage structural and computational insights not just to explain receptor–ligand interactions after the fact, but to forecast outcomes and design ligands with new properties? That’s the mission of Dr. Jens Carlsson , Professor of Computational Biochemistry at Uppsala University. His lab sits at the crossroads of structure-based modeling, computational chemistry, and drug discovery —rethinking how simulations, docking, and machine learning can transform GPCR research from descriptive science into predictive decision-making. From Static Structures to Testable Hypotheses Carlsson’s philosophy is simple but radical: modeling should generate hypotheses, not just rationalize data. Projects in his group often begin with either: A new GPCR structure  ripe for exploration, or A pharmacological challenge  such as differentiating agonists from antagonists, predicting biased agonism, or achieving receptor subtype selectivity. To tackle these, the lab employs molecular docking, molecular dynamics simulations, and ligand-based screening . Vast chemical libraries—sometimes billions of molecules—are sifted computationally to highlight potential hits. When existing compounds are exhausted, bespoke ligands are designed and synthesized in-house. That medicinal chemistry capacity is unusual for a modeling lab and provides a critical bridge between prediction and validation. Every computational hypothesis moves downstream into experimental assays via close collaborations. For Carlsson, a prediction is only valid if it survives wet-lab testing.   The “Predict, Not Explain” Ethos What sets the Carlsson lab apart is its internal rule : results must be actionable. Instead of rehashing how a known ligand binds to a known receptor, they aim to produce predictions that guide experimental choices —whether in target prioritization, compound selection, or mechanistic exploration. This predictive framing raises the bar. Common questions in the group include: Can we forecast ligand efficacy or selectivity? Can we design compounds that trigger biased signaling? But part of their rigor lies in restraint. If a method can’t resolve subtle potency differences, the team prefers to acknowledge that limitation rather than overpromise. That scientific humility has earned credibility with experimental collaborators , where skepticism of computational work is common.   GPCR Modeling in Context: Then and Now When Carlsson entered the GPCR field in the early 2000s, structural data was scarce. His early Adenosine 2A receptor work, in collaboration with Ken Jacobson, helped establish virtual screening as a viable tool for GPCR ligand discovery. Fast forward to today: dozens of GPCR structures  exist, many in multiple conformations or bound to G proteins and arrestins. Yet functional selectivity, allosteric modulation, and biased agonism  remain major challenges. Carlsson’s group integrates modeling with mechanistic pharmacology. For dopamine receptor studies, they built predictive models before experimental structures were available. When crystal structures were finally solved, the models aligned strikingly well—a rare and powerful validation.   AlphaFold: A Game-Changer with Caveats One of the newest tools in the lab’s arsenal is AlphaFold , DeepMind’s AI-powered protein structure prediction platform. Carlsson’s team has already published cases where AlphaFold-derived GPCR models provided accurate scaffolds for ligand docking—enabling progress in systems without experimental structures. In one instance, an AlphaFold prediction was so strong the group pivoted its entire workflow around it. But AlphaFold is not a panacea. It struggles with ligand-bound conformations, GPCR–G protein complexes, and receptor–peptide interactions. The lab has witnessed both spectacular accuracy and puzzling failures. Carlsson’s takeaway: AlphaFold is a powerful starting point, but domain expertise and experimental grounding remain indispensable.   Translational Impact for Drug Discovery While the Carlsson lab is rooted in academia, its impact extends into biotech and pharma. Carlsson also runs a consulting arm  that advises drug discovery teams on GPCR modeling strategy. Notably, this isn’t contract computational chemistry—it’s strategic guidance  on target selection, ligand feasibility, and prioritization. This dual perspective makes Carlsson a trusted partner for industry teams navigating early-stage pipelines , where skepticism toward in silico hits is high. By focusing on translationally relevant predictions , the lab helps bridge the gap between computation and experiment. For drug discovery executives, the message is clear: predictive modeling can shorten timelines, reduce costs, and expand druggable space—if it’s done with rigor and honesty.   Why Predictive GPCR Modeling Matters Now The convergence of machine learning, improved GPCR structures, and scalable experimental assays is shrinking the gap between modeling and pharmacology. But success depends on researchers who can manage expectations, build trust, and integrate across disciplines. Carlsson’s group does not aim for perfect predictions. Instead, it aims for useful, testable predictions that shape the next experiment. That shift—from describing the past to forecasting the future—is what makes predictive GPCR modeling transformative. For scientists, this is an intellectual challenge: demand more from your models. For industry leaders, this is an operational opportunity: integrate prediction into decision-making.   Modeling That Moves the Field Forward The Carlsson lab exemplifies how c omputational biochemistry can meaningfully impact real-world pharmacology. With rigor, transparency, and cross-disciplinary collaboration, they’re pushing GPCR science toward a predictive era. The next frontier in GPCR drug discovery isn’t more structures—it’s smarter models. Are you demanding enough from yours? Want to go deeper into GPCR modeling? Dr. Jens Carlsson breaks down the tools, challenges, and mindset behind building models that don’t just explain—they predict . 🎧 Listen to the full episode of the Dr. GPCR Podcast Push the boundaries of what's possible 👉 Join the Dr. GPCR Premium Ecosystem  for advanced insights into structure-based modeling, ligand design, and experimental collaboration. 🧠 Learn from the field’s top innovators. 📈 Sharpen your translational impact. 🔗 Connect with scientists shaping the future.

Why Speed Matters in GPCR Drug Discovery Nine out of ten GPCR programs stall  not because the target was wrong, but because teams waited too long to test the right thing. Terry has seen this story play out for 40 years — and he’s helping rewrite the ending. In accelerating GPCR drug discovery, the bottleneck isn’t target identification — it’s turning validated hits into real therapies fast. Attrition rates in early pharmacology remain painfully high. Molecules that look promising in vitro often unravel in vivo. Programs stall. Timelines stretch. But what if you could navigate these bottlenecks using the field-tested decision logic  of one of the most experienced pharmacologists alive? That’s exactly what Terry’s Corner  was built to do: bring four decades of frontline discovery insight straight to discovery-phase scientists and R&D strategists — without the noise, hype, or outdated models. In this session, you’ll gain: ✅ Proven strategies  to balance in vitro vs. in vivo testing early — when it matters most. ✅ Practical ways  to integrate kinetics, allostery, and bias into smarter development decisions. ✅ Insider guidance  on how real teams decide which GPCR programs to advance or kill. The High Cost of Pharmacology Gaps Every experienced drug hunter knows this: validation isn’t the problem anymore. Screening technologies, structure-informed design, and AI are accelerating target selection. The real friction point lies downstream : translating receptor–ligand interactions into actionable development decisions. A well-behaved molecule in a dish can fail spectacularly in vivo, leaving teams with years of sunk costs and little to show for it. Terry puts it bluntly: “Once you have a molecule, everything boils down to pharmacology—hit, lead, candidate, drug. And the rate of attrition in these steps is still atrocious.” Terry’s Corner is designed to shorten that distance between initial promise and actionable clarity. Scientists get frameworks, not guesswork. Early In Vivo Wins the Race When is the right time to move beyond cell assays? Earlier than many teams do. “The sooner you get your molecule in vivo, the sooner you know whether anything’s happening—and whether it’s the right or wrong thing,” Kenakin emphasizes. In vitro work is invaluable for mechanistic understanding—assay volume control, expression system contrasts, predictive pharmacology. But in vivo testing reveals the physiological truth . A smart program doesn’t wait until late stages to validate its assumptions. GPCR Kinetics: The Critical Data You Can’t Afford to Skip Equilibrium potency data only tells part of the story. Real systems don’t live at equilibrium. “Target residence time in vivo correlates beautifully with activity. Potency does not,” says Kenakin. High-throughput screens and static binding curves are easy to run, but ignoring kinetic profiling  means missing the factors that often make or break clinical efficacy. Modern real-time assays can deliver these insights earlier, faster, and cheaper than most teams assume. Kinetics isn’t an afterthought—it’s a competitive advantage . Allostery Is Not Optional Anymore The GPCR field is no longer a binary world of agonists and antagonists. “GPCRs are nature’s prototype allosteric proteins. Everything they do is allosteric.” Allosteric modulators and biased ligands aren’t exotic outliers—they’re increasingly common outcomes of modern screening. Teams that don’t understand how to detect, interpret, and exploit these mechanisms risk walking away from valuable compounds. Kenakin reminds us: “Allostery will seek you—even if you don’t seek it.” Antibodies, Bias, and the Expanding Modality Landscape Antibody therapeutics are now entering spaces once dominated by small molecules. Biased antibodies and allosteric antibody modulators are no longer theoretical—they exist. This expands the strategic toolbox for discovery teams: Bias isn’t an “optional property” to design in later. It shows up naturally. Allosteric antibodies can mirror or exceed small molecule complexity. Early cross-screening can flag biased phenotypes long before animal studies. How CRO Communication Impacts GPCR Drug Development Success Even the best science falters without operational precision. CRO partnerships are essential for most discovery programs, but they often break down on communication . “Scientists love to control experiments. CROs have standard ways of doing them. You must bridge that gap,” Kenakin notes. Teams that proactively define experimental nuances early avoid receiving “perfectly executed wrong assays.” Every misaligned study is not just wasted budget—it’s lost time. Program Kill vs. Advance: What Real Teams Do How do large pharma teams decide whether to advance or pause a GPCR program? It’s less bureaucratic than most outsiders think. Programs aren’t killed because of bad ideas—they’re paused when the chemical matter isn’t compelling enough or when strategic focus shifts. “In industry, scientists bring targets forward. There’s no central committee handing down orders. Grassroots science drives the agenda.” For scientists in discovery, this means two things: Technical clarity drives survival. Strategic communication drives momentum. Key Questions Answered in this AMA Session How early in vivo models sharpen go/no-go calls. Why kinetic profiling matters more than most teams realize. How to embrace (not fear) allosteric complexity. What happens inside Big Pharma when programs are paused or advanced. How better CRO communication prevents costly errors. 👉  Join Terry’s Corner & Secure Your Spot for the October 30 AMA Why Terry’s Corner Terry’s Corner  is a living, growing knowledge hub led by Terry Kenakin—a world authority in pharmacology. Here, you’ll get: Weekly lectures  that sharpen your command of how enzyme activity drives pharmacokinetics and drug design. A growing on-demand library  where enzyme inhibition, activation, and metabolism are demystified with clarity you can act on. Monthly AMAs  where you can challenge Dr. Kenakin with your own enzyme or GPCR interaction puzzles. Direct input  on future sessions—so topics match the hurdles your team faces in discovery and development. Decades of kinetic insight  reframed into actionable tools for faster, cleaner decision-making. Every molecule tells a story about how it binds, signals, and behaves. This AMA helps you read that story faster, so you don’t just generate data—you generate direction. 🟢 40 years of expertise at your fingertips:   Explore the complete library ➤ ✳️ Want to know what’s inside?   Read the latest articles ➤ Stay sharp between lectures.   Subscribe to The Kenakin Brief  today ➤

📰 GPCR Weekly News, July 29 to August 4, 2024 Hey there, readers! Take a look at our GPCR coverage for this week. We've got 11 GPCR papers, seven industry news pieces, a new GPCR event, and even a job ad.   This week's highlight includes congrats to: Miles Thompson , Alexander Hauser , Caroline Gorvin ,   et al.   for their work on GPCR gene variants and human genetic disease Ilana Kotliar , Thomas Sakmar , et al. for their study on Multiplexed mapping of the interactome of GPCRs with receptor activity-modifying proteins Nicholas Kapolka , Geoffrey Taghon , and Daniel Isom  for their research on Advances in yeast synthetic biology for human GPCR biology and pharmacology Dr. GPCR University Early-Bird Registration Open for Premium Members! Unlock a 25% exclusive discount on these courses with Dr. Terry Kenakin with our premium membership and enjoy a 1-month FREE trial! Don’t miss out—secure your spot today! Registrations for the public will be on Monday! Hurry! Courses Schedule and  Benefits Every Thursday at 10 am EST Online Lectures 1:1 meeting with Dr. Terry Kenakin Reading Materials Access to the private group Certificate of participation Learn the essentials: Measuring the pharmacologic activity of ligands (affinity, efficacy, co-operativity) Determining mechanisms of action for new GPCR ligands Elements of a comprehensive and effective GPCR discovery Master advanced applications: Using new cellular assays to analyze GPCR ligand behavior Predicting activity and in vivo target coverage with real-time kinetics Discovering new ligands and GPCR behaviors for unique drug profiles   GPCR Event Highlight 11th Adhesion GPCR Workshop Join us in vibrant Mexico City from October 23-25, 2024, to connect with fellow scientists and explore the latest in adhesion GPCR biology. Logo Contest : Let your creativity shine by submitting your design for the Logo Contest before August 15, 2024 Sponsorship Opportunities :   Elevate your brand's presence at this scientific event . Contact us at Hello@DrGPCR.com   to learn more. Your participation is eagerly awaited!  Let’s dive into the   Classified GPCR News  from July 29th to August 4th, 2024 GPCR Activation and Signaling ONE-GO: Direct detection of context-dependent GPCR activity Multiplexed mapping of the interactome of GPCRs with receptor activity-modifying proteins Molecular mechanism of bitter taste receptor agonist-mediated relaxation of airway smooth muscle GPCR Binders, Drugs, and more Expanding Structure-Activity Relationships of Human Urotensin II Peptide Analogues: A Proposed Key Role of the N-Terminal Region for Novel Urotensin II Receptor Modulators GPCRs in Oncology and Immunology G protein-coupled receptor-mediated signaling of immunomodulation in tumor progression Methods & Updates in GPCR Research GPCR Signaling: A Study of the Interplay Between Structure, Energy, and Function Engineering a GPCR-based yeast biosensor for a highly sensitive melatonin detection from fermented beverages The calcium-binding photoprotein clytin II: Expression of the preferred human codon-optimized clytin II gene in Chinese hamster ovary-K1 cells and its use in the G-protein-coupled receptor assays Predicting the Hallucinogenic Potential of Molecules Using Artificial Intelligence Reviews, GPCRs, and more G protein-coupled receptor (GPCR) gene variants and human genetic disease Advances in yeast synthetic biology for human G protein-coupled receptor biology and pharmacology Industry News Muscarinic drugs breathe new life into schizophrenia pipeline GPCR Dynamics Reveal Mechanisms for Drug Discovery DMS: Linking Protein Structure To Function AbbVie Completes Acquisition of Cerevel Therapeutics Nxera Pharma attended the Drug Discovery Ecosystem Summit Tectonic Therapeutic Announces Closing of Merger with AVROBIO as well as Concurrent Private Placement of $130.7 Million Tectonic Therapeutic Announces US IND Clearance for Lead Program, TX45   GPCR Events, Meetings, and Webinars September 18, 2024 | FREE Webinar - The value of GPCR cell-based assays in drug discovery October 2024 | Biologics US 2024   October 2 - 4, 2024 | 9th GPCRs in Medicinal Chemistry NEW October 17, 2024 | Unprecedented fragment-based screening using Spectral Shift for GPCRs October 23 - 25, 2024 | 11th Adhesion GPCR Workshop November 5 - 7, 2024 | 16th Annual PEGS Europe   July 12 - 17, 2026 | 20th World Congress of Basic and Clinical Pharmacology GPCR Jobs NEW Postdoc in GPCR mechanosensing   Postdoctoral Position Postdoctoral research position Senior or Lead Researcher   Senior Scientist, Cryo-Electron Microscopy   Postdoctoral Research Associate Join Dr. GPCR Ecosystem

Watch Episode 175 From failed assays to breakthroughs in GPCR modeling , Dr. Jens Carlsson’s path into science was anything but straightforward. When he first began working in a lab, success seemed elusive: experiments often failed, and bench work felt unnatural. At one point, he even questioned whether research was the right career for him. The turning point came from an unexpected source: a letter of recommendation. A professor highlighted Carlsson’s talent in molecular modeling, a skill he hadn’t yet recognized as central to his future. That recognition shifted everything. Today, Carlsson is a Professor of Computational Biochemistry at Uppsala University and one of the most respected voices in GPCR modeling , where his group uses structure-based techniques not just to explain experimental results but to predict them.   Finding Science Through Serendipity Carlsson didn’t grow up with a vision of becoming a scientist. Raised in a small town in southern Sweden, he had never met anyone with a PhD and had little exposure to research. When he moved to Uppsala in the late 1990s to study engineering, it was biotechnology—then on the rise—that caught his interest. Inspired by news stories about breakthroughs like the cloning of Dolly the sheep and genetically modified foods, he saw life sciences as a field full of promise. Still, early research internships were rocky. A summer spent purifying proteins highlighted his discomfort at the bench. While others refined lab techniques, he found himself gravitating toward structural models in his spare time. He was naturally drawn to analyzing solved protein structures—an activity that, unbeknownst to him, was laying the groundwork for a future in computational modeling.   Discovering Modeling (and GPCRs) by Accident That interest led him to pursue a thesis at Scripps Research in San Diego, where he focused on how proteins respond to pH changes using molecular simulations. It was the first time he found himself immersed in a computational environment, and he realized how much he enjoyed the intellectual energy of modeling communities. When he returned to Sweden for his PhD, he focused on small molecule design. At the time, there were no solved structures of GPCRs readily available, so his work remained disconnected from that target class. It wasn’t until his postdoctoral years at UCSF—under Brian Shoichet—that GPCRs entered his scientific view. His introduction came through a practical suggestion: explore a new protein family that was gaining traction in the structural biology world. At that point, very few GPCR crystal structures had been determined. This scarcity made the field both exciting and high-risk. With limited structural data but a growing pharmacological interest, GPCRs presented the perfect challenge for someone who wanted to build predictive models from scratch.   Predictive GPCR-Ligand Modeling Carlsson's work quickly shifted from curiosity to impact. One of his early projects involved the A2A adenosine receptor, a GPCR with known relevance in diseases like Parkinson’s. Using virtual screening, he was able to identify novel ligands that aligned with experimental findings. This success was a revelation—it was possible not only to interpret experimental data but to forecast  it through modeling. This realization sparked a new guiding principle: computational tools should aim to predict experimental outcomes. For Carlsson, this marked a shift in how his lab approached GPCR research. Rather than focusing solely on explaining receptor behavior post hoc, his group began developing workflows and strategies that could drive experimental design forward.   Bridging Computation and Collaboration While Carlsson began his scientific career with a deep skepticism about collaborations—particularly with experimentalists—his experiences in the GPCR field forced a reevaluation. He came to see that effective GPCR research requires true interdisciplinary integration. Collaborating with chemists, biologists, and pharmacologists not only made his predictions more useful, but also shaped the kinds of questions his lab could ask. Today, his group includes around ten computational chemists and one in-house medicinal chemist. The division of labor reflects a pragmatic approach to problem-solving. While early stages of a project often rely on virtual screening from commercial compound libraries, the work inevitably reaches a point where novel, non-commercial ligands are needed. This is when the synthetic expertise of the chemist becomes essential. Pharmacology, on the other hand, is often outsourced through collaborations with expert labs who specialize in particular receptors. Carlsson notes that it’s easier to find pharmacologists to run assays than it is to persuade chemists to synthesize new compounds based on computational predictions—a sentiment that highlights the skepticism that still exists around modeling in some corners of drug discovery.   Embracing Complexity and Failure Carlsson’s approach to modeling is rooted in scientific humility. He emphasizes that not every question can be answered computationally—and that saying “we don’t know” is a valid, and often necessary, scientific position. When asked whether a compound is twice as potent as another, he’s quick to point out the limitations in both experimental and computational resolution. This perspective influences how his lab trains students. It's not enough to run simulations or generate models. Trainees must learn how to interpret assay data, understand pharmacological context, and communicate across disciplines. Many of his former students now work in industry, where their ability to bridge the computational-experimental divide makes them highly valuable.   Career Lessons for Young Scientists Carlsson’s journey holds several lessons for early-career researchers. First and foremost: follow the questions that keep you up at night. He believes genuine interest—not trends or external validation—is what sustains long-term scientific productivity. The daily failures and rejections of research require an intrinsic motivation that goes beyond job titles or metrics. He also underscores the importance of mentorship—not just for guidance, but for perspective. Good mentors help shape thinking without prescribing decisions. For Carlsson, influential mentors helped him find confidence in his own scientific voice while remaining open to other perspectives. Finally, he advises young scientists to celebrate small wins. In a field where major publications and grant awards can be rare, finding satisfaction in an optimized curve, a new insight, or a well-modeled structure is what keeps momentum going.   AI and the Future of GPCR Modeling Carlsson is excited by the potential of tools like AlphaFold  and the continued evolution of AI in structure prediction. His lab has already begun using AlphaFold models to identify ligands for targets that lack experimental structures. While these tools aren’t perfect—and sometimes fail in unexpected ways—they represent a shift in what’s possible. Still, he emphasizes that data limitations remain a major challenge, especially when it comes to small molecule prediction. Unlike protein sequences, small molecule data are often fragmented, inconsistent, or unavailable, making model training more difficult. Until better datasets emerge, predictive modeling will continue to rely on creative integration of computational and experimental insights.   Modeling a Career on Your Own Terms Carlsson’s career shows that failures can evolve into strengths and that computational insights can transform how we approach GPCRs. As predictive modeling matures, its role will continue to expand, guiding ligand discovery, informing pharmacology, and accelerating translation into the clinic. For early-career researchers, the takeaway is direct: GPCR drug discovery will increasingly depend on those who can unite modeling with experimentation, turning predictions into real therapeutic breakthroughs. Hear the full conversation with Jens Carlsson 🎧 Catch the full episode on the Dr. GPCR Podcast 💡 Stay curious. Stay connected. Looking for more insights like this? 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Molecular innovation This Week’s GPCR Intelligence: The next edge in discovery isn’t louder exposure—it’s smarter engagement. This week’s Dr. Kenakin from Terry's Corner shows how to tame irreversible drugs so their kinetic power works for you, not against you. You’ll get a framework to predict duration, penetration, and PK/PD separation—so decisions move faster and risks surface earlier. Breakthroughs this week:  nanomedicines targeting PAR2 for sustained analgesia; Emerging Voices in GPCR Biology; Domain Therapeutics patents new PAR2 antagonists. 🔍 This Week in Dr. GPCR Premium: Sneak Peek Industry insights:  Confo VLAIO grant; Skye CB1 Ph2 miss; Chugai CT-388 in-license; Septerna valuation. Upcoming events:  Membrane-mimetic screening; GPCR Forum 2025; GPCR-TDD Summit Europe. Career opportunities:  Sr. Scientist—In-vitro Pharm; Postdoc roles. Must-read publications:  AT1R β-arrestin bias; UII receptor structure; β2AR constant-pH dynamics. Terry's Corner – Control Target Engagement—Don’t Chase It with Irreversible Drugs When binding outlives exposure, everything changes. This feature frames how to define “irreversible” in real systems, anticipate PK/PD separation, and use target turnover to tune duration. You’ll see why tight binding can backfire on tissue penetration, where k_inact/K_I beats classic Ki, and how to quantify what matters—speed of inactivation and durability of effect. If your team is designing covalent or tight-binding candidates, these principles reduce surprises and accelerate dose optimization. You’ll avoid costly missteps by: Preventing kinetic traps —spot PK/PD decoupling early so washouts and C_max don’t mislead dosing strategy. Designing for penetration —balance on/off rates to reach inner tissue, not just peripheries. Quantifying what counts —prioritize k_inact and k_inact/K_I to compare irreversible inhibitors realistically. 🎥  Live AMA with Dr. Kenakin — October 30, 12 PM EST   Join Dr. Kenakin live and bring the questions that keep you thinking. Each AMA feeds directly into next month’s lessons—your real-world challenges shape what comes next.   Your Membership Gives You: Proven frameworks used in real discovery programs On-demand lessons built for tight research schedules A say in the topics covered next Weekly updates that keep your knowledge sharp Monthly live AMAs with Dr. Kenakin Trusted insights from biotech, pharma, and academia 🎬 Plus New: Lesson Trailers   Curious about Terry’s Corner before committing? Watch our new trailers for a preview of expert-led GPCR training designed for scientists and drug hunters.    💎  $2,999/year — the cost of one conference = a year of expert training — Premium Members Enjoy Over 50% Discount at Checkout Get Yearly Access On-Demand Now — Free 7 Day Trial ➤ DrGPCR Podcast: Jens Carlsson on Predictive Modeling Prediction over explanation—that’s the shift. Jens Carlsson shares how structure-based design, molecular dynamics, and smart collaboration turn models into decisions, with practical guardrails on AlphaFold’s limits. Ideal for scientists who want modeling to guide experiments, not just narrate them. Value at a glance: From screens to hits —how to identify novel GPCR ligands with structure-based workflows. Know the limits —where AI helps and where it still overpromises. Bridge the aisle —modelers × experimentalists for faster iteration. Listen to the episode ➤ Why Dr. GPCR Premium Membership Gives You an Edge Premium provides scientists with weekly expert lectures, industry updates, priority events, targeted roles, and editorial context, allowing proactive action before signals become headlines. It’s an operating system for discovery decisions, featuring practical frameworks, trusted curations, and a community that accelerates your progress. Staying current is essential as kinetics, structure, and signaling evolve rapidly. Premium keeps you oriented and out of avoidable dead-ends. 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Watch Episode 174 You never forget the day your data surprises you—in a positive way. For Dr. Eric Trinquet, that moment arrived when his team successfully tracked GPCR internalization in native beta cells. They achieved this without complex imaging or radioactive materials. It was simply a clean, scalable assay—and a wave of new possibilities. This success was not mere luck. It was the result of chemistry, collaboration, and relentless effort until the signal finally confirmed: “We’re in.” From Bench to Breakthrough: Why pHSense Matters Decades of GPCR research have relied heavily on engineered systems. These include overexpression, tags, and fluorescent imaging. While they produce impressive data, they also impose artificial constraints. What if you could directly measure receptor internalization in physiologically relevant cells without disrupting their native state? That’s the promise of pHSense, a groundbreaking reagent developed by Eric Trinquet and his team at Revvity. This innovation emerged from years of foundational work in photophysics and GPCR pharmacology. Instead of creating another black-box assay, they designed pHSense around rare-earth europium probes. These probes shift brightness and fluorescence lifetime as pH changes. It’s a subtle yet powerful innovation. These probes become brighter and have a longer lifespan as internalized receptors enter acidic endosomes—translating biology into signal, instantly and accurately. Why does this matter? Until now, visualizing GPCR trafficking required imaging or forced overexpression. pHSense offers a high-throughput, no-wash, plate-reader-compatible assay with real-world relevance. The Chemistry That Almost Didn’t Work Designing pH-sensitive rare-earth complexes was not an obvious choice. The chemistry involved is notoriously complex. Solubility poses significant challenges. Even minor adjustments can compromise photophysical properties. However, Trinquet’s team, in collaboration with Professor David Parker from Durham University, cracked the code. They learned how to fine-tune both brightness and fluorescence lifetime. This led to the creation of a two-dimensional pH response curve capable of detecting subtle endosomal acidification. “You’re not changing the spectrum. You’re just changing how bright it is—and how long it glows,” said Dr. Eric Trinquet. Once they identified a lead compound, it became evident: this was not just another probe. This was the foundation of a new set of assay tools. The Day It Worked — Without Overexpression Trinquet describes this as a cornerstone moment. After months of adjustments, a scientist on his team presented a data set that transformed everything: a clean, dose-dependent response of GLP-1 receptor internalization in native beta cells. No imaging. No genetic modification. Just a plate reader, an agonist, and an endogenous GPCR. This achievement was not only technically impressive; it was conceptually transformative. For the first time, a team demonstrated high-throughput internalization data in physiologically relevant cells. Behind Every Probe Is a Partnership While the final product may arrive neatly packaged, the journey behind pHSense was anything but straightforward. The chemistry originated from Parker’s lab. The biological validation came from Jean-Philippe Pin’s group at the Genomic Functional Institute in Montpellier. The Revvity team acted as the glue. They constructed the platform, tested every variable—pKa, brightness, lifetime—and made decisions that few would even consider measuring. These were not mere vendor-supplier relationships. They were collaborative scientific ventures, years in the making. The outcome is not just a probe; it’s a tool scientists can trust. Mini Timeline: pHSense Development Early 2020s: Rare-earth probe synthesis begins Collaborative screening of scaffold families Key milestone: Clean signal in endogenous beta cells Revvity commercial launch Building a Scalable Platform — Not a One-Off Assay The brilliance of pHSense lies not only in the chemistry but also in its modularity. The assay is compatible with SNAP-tags, FLAG-tags, HA-tags, and even antibody fragments for native GPCRs. Whether in industry or academia, whether overexpressing or not, you can adapt the assay to your system. Since it operates on plate readers without wash steps, it is suitable for full-scale compound screening. “Don’t chase the shiny imaging tool if it doesn’t scale. Build or adopt assays that can evolve with your questions—like pHSense.” What’s Next? Follow the Feedback For Trinquet, commercialization is not the end; it’s a new beginning. User feedback will guide the development of future tags and variants. Teams are already investigating temperature effects, biased signaling, and endogenous dynamics. There is excitement about combining pHSense with other HTRF assays for multi-pathway mapping—G protein, arrestin, internalization—on the same cell line. What started as a chemistry problem has evolved into a discovery platform. “It’s like a funnel,” Trinquet explains. “You start wide with chemistry, you narrow with biology, and at the end—if you did it right—you open new doors.” To hear the full story of how pHSense came to life—and why the GLP-1 data changed everything— 🎧 Listen to the full podcast episode here ⸻ More about Revvity pHSense Reagents GPCR Reagents Revvity on Dr. GPCR   Dr. GPCR X Revvity Collaboration ⸻ Want more like this? 👉 Join the Dr. GPCR Premium Ecosystem for behind-the-scenes access to GPCR innovators, exclusive deep-dives, and practical tools to accelerate your research or career. 👥 Build connections. 🧪 Get insights. 🎧 Stay ahead.

Get ready for an expedition, GPCR explorers! Embark on another exciting exploration of the unknown realms of GPCR research. Welcome back to your weekly GPCR quest! This Week’s Highlights: Congrats to: John Teye Azietaku , our great contributor, for his article Class B1 GPCR Dimerization: Unveiling Its Role in Receptor Function and Signaling Sonja Peter , Brian Bender , Chris De Graaf for their excellent work on Comparative Study of Allosteric GPCR Binding Sites and Their Ligandability Potential Today, we started the Principles of Pharmacology II course! Thank you to all participants in Dr. Terry Kenakin's educational initiative this fall! Your dedication has greatly enriched the learning experience. Let’s keep fostering a collaborative environment for sharing ideas and expanding knowledge! Classified GPCR News  Let’s dive into the   Classified GPCR News from October 21st to 27th, 2024 Industry News Call for GPCR Papers Deadline: Nov 1, 2024. Emerging Voices in GPCR Biology in Special Issue of Molecular Pharmacology GPCR Events, Meetings, and Webinars November 5 - 7, 2024 | 16th Annual PEGS Europe   November 25 - 27, 2024 | 1st Virtual GPCR Forum Conference November 26 - 28, 2024 | GPCRs-Targeted Drug Discovery Summit Europe July 12 - 17, 2026 | 20th World Congress of Basic and Clinical Pharmacology GPCR Jobs Scientist I Cell Biology - Tectonic Therapeutic Senior Scientist, GPCR Pharmacology Research Associate - Professor Graeme Milligan Postdoc in Molecular Pharmacology - The Hauser Group Postdoctoral Scholar – iPSC in cardiac and endothelial cell function Protein Biochemist/Structural Biologist Senior Scientist/Staff Scientist, Computational Chemistry Postdoc in GPCR mechanosensing   GPCR Activation and Signaling A gain of function variant in RGS18 candidate for a familial mild bleeding syndrome Fusarium graminearum Ste2 and Ste3 Receptors Undergo Peroxidase-Induced Heterodimerization when Expressed Heterologously in Saccharomyces cerevisiae The beta 2 adrenergic receptor cross-linked interactome identifies 14-3-3 proteins as regulating the availability of signaling-competent receptors GPCRs in Neuroscience Astrocyte Gi-GPCR signaling corrects compulsive-like grooming and anxiety-related behaviors in Sapap3 knockout mice Orphan GPCRs in Neurodegenerative Disorders: Integrating Structural Biology and Drug Discovery Approaches Altered PLCβ/IP3/Ca2+ Signaling Pathway Activated by GPRCs in Olfactory Neuronal Precursor Cells Derived from Patients Diagnosed with Schizophrenia Sphingosine 1-phosphate receptor subtype 1 (S1P1) activity in the course of Alzheimer's disease GPCRs in Oncology and Immunology Characterization, expressional and evolutionary analysis of five fish-specific CCRs (CCR4La, CCR4Lc, CCR12a1, CCR12a2, and CCR12b) in largemouth bass (Micropterus salmoides) The pyruvate-GPR31 axis promotes transepithelial dendrite formation in human intestinal dendritic cells Methods & Updates in GPCR Research Generation of CRISPR/Cas9 modified human iPSC line with correction of heterozygous mutation in exon 6 of the CaSR gene Reviews, GPCRs, and more Insight into structural properties of viral G protein-coupled receptors and their role in the viral infection: IUPHAR Review 41 Structural and Molecular Insights into GPCR Function Comparative Study of Allosteric GPCR Binding Sites and Their Ligandability Potential Molecular Dynamics (MD) Simulations Provide Insights into the Activation Mechanisms of 5-HT2A Receptors Investigating the Effect of GLU283 Protonation State on the Conformational Heterogeneity of CCR5 by Molecular Dynamics Simulations Become a Premium Member! Get your 5-day free trial TODAY!

Greetings, Pioneers of GPCR Science! Embark on this week’s thrilling updates in GPCR research, learning opportunities, and industry developments. Don’t just stay informed—immerse yourself, expand your knowledge, and become a trailblazer in the field! This Week’s Highlights: Celebrating Excellence: Wessel A. C. Burger , Arthur Christopoulos , David M. Thal , et al., for their groundbreaking work on Positive allosteric modulation of a GPCR ternary complex Unlock Your Learning: Limited Spots Available! There are only 5 spots left for our upcoming courses, so seize the chance to learn from the best in the field. 🚨 Hurry to reserve your spot for the Principles of Pharmacology I & II BUNDLE before the Early Bird Deadline on September 27 . With just one week left, becoming a premium member is all it takes to benefit from this discount! Not a premium member yet?  No worries – you can sign up for a 5-day FREE trial! Gain access to over 500 minutes of recorded classes in our  GPCR courses   taught by Drs. Terry Kenakin  and Sam Hoare ! Every Thursday at 10 AM EST: Principles of Pharmacology I Dates: October 3, 10, 17, 24 (four sessions) Topics: Pharmacologic activity measurement, mechanisms of action, and GPCR discovery strategies. Registration deadline: September 27, 2024 Principles of Pharmacology II Dates: October 31, November 7, 14, 21, December 5 (five sessions) (we skipped Thanksgiving, of course!) Topics: New cellular assays, real-time kinetics, and unique GPCR behaviors. Registration deadline: October 25, 2024 🔥 Why You Should Enroll Now: Cost-effective & Distinctive Educational Experience Affordable courses that maintain high-quality standards. Adaptable Learning Access recorded sessions at your convenience to enhance your understanding. Our Students Highly Recommend Us! Previous students praise the course content and our exceptional service. Join us for an exciting discussion with Dr. Terry Kenakin to gain insights and prepare for upcoming courses. Don't miss this valuable opportunity! Exclusive Deal for Scientists Residing and Working in Developing Nations If you live and work  in a developing country, please complete this form to enjoy complimentary access to Dr. Kenakin's upcoming courses. Our goal is to ensure that education is within reach for everyone! Secure your spot today and dive into the evolving world of GPCRs! GPCR Event Spotlight Discovery on Target’s 19th Annual GPCR-Based Drug Discovery Targeting G Protein-Coupled Receptors for New Therapeutic Options 📍  Boston, MA 📅 October 2 -3, 2024 Join leading scientists to investigate the most recent advancements in GPCR-targeted drug development, incorporating machine learning, innovative biophysical methods, and medicinal chemistry. Register today for the GPCR Drug Discovery Conference and save $200 with discount code “ DRGPCR24 ”. 11th Adhesion GPCR Workshop    📍  Mexico City 📅 October 23-25, 2024 Engage with your peers and delve into the latest developments in adhesion GPCR biology. The full agenda is now available; check it here ! If you want to enhance your brand, email Hello@DrGPCR.com  for sponsorship opportunities. Classified GPCR News  Let’s dive into the   Classified GPCR News from September 9th to 15th, 2024 Industry News MBX aims for $136M IPO to take potential rival to Ascendis' Yorvipath into phase 3 Certa Therapeutics Announces International Non-Proprietary Name for its First-in-class GPR68 Inhibitor Asengeprast (FT011) AlphaProteo generates novel proteins for biology and health research Innovate UK announced the winners of its Transforming Cancer Therapeutics grant, which focuses on developing life-changing cancer treatments. 𝗦𝘂𝗺𝗺𝗮𝗿𝘆 𝗼𝗳 𝘁𝗵𝗲 𝗿𝗲𝘀𝘂𝗹𝘁𝘀 𝗼𝗳 𝗔𝗘𝗙𝟬𝟭𝟭𝟳 𝗣𝗵𝗮𝘀𝗲 𝟮𝗯 𝗶𝗻 𝗖𝗨𝗗 Nxera Pharma’s Partner Centessa Announces Positive Interim Phase 1 Clinical Data with its Novel Orexin Receptor 2 (OX2R) Agonist, ORX750, in Acutely Sleep-Deprived Healthy Volunteers Cumulus raising $50M, spinning GPR68 small molecules into GIO New treatments being developed for schizophrenia Crinetics Pharmaceuticals Announces September 2024 Inducement Grants Under Nasdaq Listing Rule 5635(c)(4) Call for GPCR Papers Deadline: Nov 1, 2024. Emerging Voices in GPCR Biology in Special Issue of Molecular Pharmacology GPCR Events, Meetings, and Webinars September 5 - 6, 2024 | 4th Transatlantic ECI GPCR Symposium September 18, 2024 | FREE Webinar - The value of GPCR cell-based assays in drug discovery September 22, 2024 | Biomolecular Horizons 2024 September 30 - October 3, 2024 | 22nd Discovery on Target October 2024 | Biologics US 2024   October 2 - 4, 2024 | 9th GPCRs in Medicinal Chemistry October 17, 2024 | Unprecedented fragment-based screening using Spectral Shift for GPCRs October 23 - 25, 2024 | 11th Adhesion GPCR Workshop November 5 - 7, 2024 | 16th Annual PEGS Europe   NEW November 25 - 27, 2024 | 1st Virtual GPCR Forum Conference November 26 - 28, 2024 | GPCRs-Targeted Drug Discovery Summit Europe July 12 - 17, 2026 | 20th World Congress of Basic and Clinical Pharmacology GPCR Jobs HIGHLIGHT Research Associate - Professor Graeme Milligan HIGHLIGHT Postdoc in Molecular Pharmacology - The Hauser Group NEW Postdoctoral Scholar – iPSC in cardiac and endothelial cell function NEW Protein Biochemist/Structural Biologist Senior Scientist/Staff Scientist, Computational Chemistry Postdoc in GPCR mechanosensing   Postdoctoral Position Postdoctoral research position Adhesion GPCRs Loss of cardiomyocyte-specific Adhesion G Protein Coupled Receptor G1 (ADGRG1/GPR56) promotes pressure overload-induced heart failure GPCR Activation and Signaling Positive allosteric modulation of a GPCR ternary complex GPCR Binders, Drugs, and more Progress on the development of Class A GPCR-biased ligands GPCRs in Cardiology, Endocrinology, and Taste CRTC1 in Mc4r-expressing cells is required for peripheral metabolism and systemic energy homeostasis Eiken syndrome with parathyroid hormone resistance due to a novel parathyroid hormone receptor type 1 mutation: clinical features and functional analysis GPCRs in Neuroscience Gain control of sensory input across polysynaptic circuitries in mouse visual cortex by a single G protein-coupled receptor type (5-HT2A) GPCRs in Oncology and Immunology The power of many: Multilevel targeting of representative chemokine and metabolite GPCRs in personalized cancer therapy GPR97 depletion aggravates imiquimod-induced psoriasis pathogenesis via amplifying IL-23/IL-17 axis signal pathway Structural and Molecular Insights into GPCR Function Exploring the constitutive activation mechanism of the class A orphan GPR20 Become a Premium Member! 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Pipeline Efficiency Meets Kinetic Power Imagine a drug that keeps working hours—or days—after it disappears from circulation. That’s the promise of irreversible drugs. But it’s also the reason a promising lead can turn toxic overnight. This session unpacks how persistent binding can either accelerate your program—or quietly kill it. That’s the power (and the peril) of irreversible drugs. These aren’t just “stronger binders.” They’re kinetic game-changers —compounds that rewrite the relationship between ligand , receptor , and physiologic outcome . Understanding how persistent binding affects receptor turnover, tissue penetration, and PK/PD relationships can give your team a strategic edge. In this lesson, you'll gain: ✅ Clarity on what “irreversible” really means  in kinetic and pharmacologic terms. ✅ Foresight to exploit persistent binding  without triggering long-term toxic liabilities. ✅ Decision speed to prioritize smarter leads  and avoid avoidable attrition. The Kinetic Edge You Can’t Afford to Ignore Steady state isn’t just about exposure anymore. When a compound’s off-rate is slower than its clearance, its biological effect outlives its plasma presence. This is the silent advantage of many successful drugs: they bind tightly or covalently , making target coverage durable  even as drug levels drop. For discovery teams, this means a shorter exposure can yield longer efficacy windows—opening doors to lower dosing frequency, better patient compliance, and more predictable outcomes. But it also means new liability surfaces : persistent effects can’t be simply “washed out” when things go wrong. That’s why this concept isn’t optional knowledge for drug hunters—it’s a competitive necessity. Why Tight Binding Isn’t Always Good News When a drug won’t let go, you can’t either. That’s the hidden liability beneath the kinetic edge. Irreversible binding isn’t a magic bullet. It’s a double-edged sword. When a drug outlives its exposure , toxic interactions can be just as persistent as therapeutic ones. Consider irreversible inhibition of cytochrome P450 enzymes— a red flag for regulators . Such interactions can disrupt metabolic detoxification and lead to delayed, systemic toxicity. Unlike reversible inhibitors, these can’t be dialed down with clearance. For teams advancing candidates, that means identifying kinetic red flags early, not after expensive safety studies. Good molecules can fail quietly at this stage —not because they’re weak, but because they’re too strong for their own good. The Tissue Penetration Trap Here’s a paradox: high-affinity, slow-offset compounds can undermine their own efficacy . When these drugs hit structured tissues (like solid tumors), they can get trapped at the periphery, leaving inner tissue underdosed. Antibody-drug conjugates and tumor-targeting antibodies have revealed this bottleneck firsthand. The on-rate/off-rate balance  matters: too tight, and penetration stalls; too loose, and efficacy dissipates. The best drug hunters learn to tune kinetic parameters  strategically—not just chase the highest affinity. It’s a design space , not a binary choice, and penetration is just the beginning. Even if your drug reaches its target, the effect it leaves behind rewrites the PK/PD playbook. Rethinking PK/PD Relationships With classical reversible drugs, effect and exposure walk hand in hand. With irreversible or tight-binding compounds, they decouple . This PK/PD dissociation  means: Drug exposure may end, but receptor occupancy remains. Washout experiments don’t tell the full story. Dose prediction models need kinetic nuance—not just Cmax and AUC. For teams running early-stage programs, recognizing this decoupling early can sharpen dose optimization  and de-risk clinical transitions . This is where theory collides with math. You can’t model irreversible binding with the usual tools. Quantifying the Unquantifiable You can’t describe irreversible binding with classic mass action law equilibrium constants alone. The metrics shift: k_inact  (rate of inactivation) replaces static Ki values. k_inact/KI  becomes the gold standard to compare potency between irreversible inhibitors. This reframes what it means to characterize potency. Instead of “how strong,” the better question is: “ how fast does this drug inactivate the target  and how long will it stay down?” Getting this wrong doesn’t just slow a program—it can mislead the entire development strategy . Designing Strategically with Irreversible Drug Binding in Mind When irreversible mechanisms are designed, not discovered by accident , they become strategic levers: Selective, durable tumor kill. Tunable kinetic selectivity. Dosing regimens aligned with biology, not just exposure. When they’re ignored, they become sources of silent failure : under-penetration, persistent off-target effects, or late-stage regulatory rejection. This is where seasoned drug hunters separate themselves from the pack—not just knowing the kinetics , but designing with them . 👉 Unlock Irreversible Drugs —  Only in Terry’s Corner! 🎥 Next Week's Release: The First AMA Session The first Ask-Me-Anything with Dr. Kenakin  will get released next month, featuring real questions from discovery scientists tackling enzyme kinetics, receptor bias, and assay design.  Want to join the next AMA on October 30? Join Terry’s Corner and get: Frameworks proven in real discovery programs On-demand lessons  designed for busy scientists Direct input  on future course topics Weekly new releases  — always fresh, always relevant Live monthly AMA  sessions with Dr. Kenakin Content trusted by biotech, pharma, and academia 💎 $2999/year — one conference cost = a full year of expert training Premium Dr. GPCR members save 50%+  with your Weekly News code. 👉  Join Terry’s Corner & Secure Your Spot for the October 30 AMA Why Terry’s Corner Pipeline risk isn’t just at the receptor—it’s upstream and downstream, in every enzyme your compound meets . Irreversible binding can turn enzyme interactions into make-or-break kinetic events. That’s why discovery teams turn to Terry’s Corner: to build strategies that anticipate these collisions instead of reacting to them too late. Here , you’ll get: Weekly lectures  that sharpen your command of how enzyme activity drives pharmacokinetics and drug design. A growing on-demand library  where enzyme inhibition, activation, and metabolism are demystified with clarity you can act on. Monthly AMAs  where you can challenge Dr. Kenakin with your own enzyme or GPCR interaction puzzles. Direct input  on future sessions—so topics match the hurdles your team faces in discovery and development. Decades of kinetic insight  reframed into actionable tools for faster, cleaner decision-making. Irreversible drugs expose where metabolism and binding collide. If you’re not designing with persistent enzyme interactions in mind, you’re building risk into your molecule from the start. This session helps you get ahead of that curve. 🟢 40 years of expertise at your fingertips:   Explore the complete library ➤ ✳️ Want to know what’s inside?   Read the latest articles ➤ Stay sharp between lectures.   Subscribe to The Kenakin Brief  today ➤

Celtarys Research Joins Dr. GPCR – Precision Tools for GPCR Assays Dr. GPCR and Celtarys Research have teamed up. This partnership aims to bring advanced chemical probe strategies to the forefront. The goal is to accelerate receptor-targeted discovery. They will showcase innovative conjugation methods. These methods will provide scientists with direct access to emerging tools and insights. Explore the partnership Multiplexing GPCR Discovery - Sakmar Lab’s Toolkit Goes Public The latest podcast features a discussion about a scalable GPCR-RAMP assay. It highlights its journey from one receptor to a cross-family toolkit. Hear from Drs. Tom Sakmar, Emily Lorenzen, and Ilana Kotliar about creating a multiplex system with DUET-tagged constructs. Their global resource is now helping labs decode GPCR biology at scale. Read the podcast article GPCR Publication Highlights βCGRP breaks the mold: Distinct signaling patterns reveal it’s more than just αCGRP’s twin. [Nature’s peptides return:](https://ecosystem.drgpcr.com/so/bdPSktt-s/c?w=cw8ae7XNuBdiMbjg4TeUw3rdv2qYhR4rv-bqGLmA948.eyJ1IjoiaHR0cHM6Ly9kb2kub3JnLzEwLjExMTEvYnBoLjcwMDcyIiwiciI6ImUyZGZlOTFjLTM5YzgtNDA5Yi04NTUyLWI5NjUwNGRlNzc4MyIsIm0iOiJtYWlsX2xwIiwiYyI6IjAwMDAwMDAwLTAwMDAtMDAwMC0wMDAwLTAwMDAwMDAwMDAwMCJ9 The B2D consortium revives biodiversity as a source for selective GPCR ligands. GPR45 steps up: A previously orphan receptor emerges as a powerful target for appetite and obesity control. Full Breakdown of the Latest in GPCR Research Want detailed insights? Dive into this week’s research, tools, and biotech updates all in one place. It’s exciting to see how the GPCR field is evolving. With the right tools, bold ideas, and powerful collaborations, you’re not just keeping pace. You’re actively shaping what’s next. Don't miss out on the opportunity to stay informed and inspired. Stay curious! The Dr. GPCR Team

Hello GPCR Trailblazers, This week, we’re spotlighting Celtarys Research, our newest partner, featured in a blog and podcast with CSO Dr. Maria Majellaro, highlighting their fluorescent ligand tools for live-cell GPCR assays.   After 40+ years and 250 publications, Dr. Terry Kenakin is launching a new learning space with video courses, AMAs, and practical insights . Get a sneak peek  and sign up for The Kenakin Brief—his free weekly newslette r.   On the industry side, Novo Nordisk, Septerna, and Deep Apple advance billion-dollar GPCR programs, while Eli Lilly and Nxera move forward in metabolic disease.   📚 This week’s paper highlights: GLP-1R/GIPR biased agonism enhances metabolic outcomes Ghrelin receptor flips D2 signaling without a ligand MOR-PAM shows G protein-selective bias   The insights are ready. The time you’ll save is yours. Terry’s Corner is coming soon. Dr. GPCR Updates Terry’s Corner Is Coming – Get Early Access and Updates    Terry’s Corner is launching soon with monthly courses, AMAs, and real-world pharmacology from Dr. Terry Kenakin. You can already explore the platform and subscribe to The Kenakin Brief—our new newsletter packed with sneak peeks, insights, and launch news straight to your inbox.   Explore Terry's Corner From Chemistry Lab to GPCR Partner – New Podcast with Celtarys Dr. Maria Majellaro of Celtarys shares how her team translates medicinal chemistry into practical GPCR assay tools—and how their new partnership with Dr. GPCR will help researchers move faster with custom fluorescent ligands, translational insight, and tool-enabled discovery. Introducing Celtarys - Probe Development via Conjugation Strategies   Celtarys Research's first article provides a detailed examination of conjugation strategies to develop high-performance fluorescent probes. It emphasizes scaffold selection, linker optimization, and assay compatibility to enhance target binding and signal fidelity in GPCR applications.    Read the full article GPCR Publication Highlights   GLP-1R/GIPR biased agonism enhances metabolic outcomes —with dual targeting showing synergistic glucose and weight benefits.   Constitutive ghrelin receptor activity, not dimerization or ligand binding —reverses dopamine D2 signaling in a physiologically critical circuit.   A MOR-positive allosteric modulator (BMS-986122) selectively enhances opioid signaling  through specific Gα subtypes, revealing new paths to safer analgesia. Want the full breakdown? Explore this week’s research, tools, and biotech insights in one place. The insights are ready. The time you’ll save is yours. Terry’s Corner is coming soon. Stay curious, The Dr. GPCR Team